US12305240B2 - Methods for colon cancer detection and treatment - Google Patents

Methods for colon cancer detection and treatment Download PDF

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US12305240B2
US12305240B2 US17/815,008 US202217815008A US12305240B2 US 12305240 B2 US12305240 B2 US 12305240B2 US 202217815008 A US202217815008 A US 202217815008A US 12305240 B2 US12305240 B2 US 12305240B2
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score
expression level
colon cancer
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Irvin Mark Modlin
Mark Kidd
Ignat Drozdov
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Liquid Biopsy Research LLC
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    • A61K31/7072—Compounds having saccharide radicals and heterocyclic rings having nitrogen as a ring hetero atom, e.g. nucleosides, nucleotides containing six-membered rings with nitrogen as a ring hetero atom containing condensed or non-condensed pyrimidines having oxo groups directly attached to the pyrimidine ring, e.g. cytidine, cytidylic acid having two oxo groups directly attached to the pyrimidine ring, e.g. uridine, uridylic acid, thymidine, zidovudine
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    • C12Q2600/00—Oligonucleotides characterized by their use
    • C12Q2600/158—Expression markers

Definitions

  • the Sequence Listing XML associated with this application is provided electronically in XML file format and is hereby incorporated by reference into the specification.
  • the name of the XML file containing the Sequence Listing XML is “LBIO-004_C01US_SeqList.xml”.
  • the XML filed is 112,806 bytes in size, and was created on Jul. 25, 2022, and is being submitted elelctronically via USPTO Patent Center.
  • the present invention relates to colon cancer detection.
  • CRC Colorectal cancer
  • CEA carcinoembryonic antigen
  • a glycoprotein involved in cell adhesion that is not generally expressed in adult tissues except in heavy smokers. Its specialized sialofucosylated glycoforms serve as functional colon carcinoma L-selectin and E-selectin ligands, which may play a role in metastatic dissemination of colon carcinoma cells.
  • CEA is principally used to monitor colorectal carcinoma treatment, to identify recurrences after surgical resection, for staging or to localize cancer spread through measurement of biological fluids. There are, however, significant limitations. While preoperative CEA levels have shown an association with (disease-free) survival, this was chiefly because it was a surrogate for metastatic presentation.
  • a 14-gene expression tool for colon cancer detection is disclosed herein.
  • the present disclosure provides a method for detecting a colon cancer in a subject in need thereof, comprising: (a) determining the expression level of at least 14 biomarkers from a test sample from the subject by contacting the test sample with a plurality of agents specific to detect the expression of the at least 14 biomarkers, wherein the 14 biomarkers comprise ADM1, CDK4, COMT, DHCR7, HMOX2, MCM2, PDXK, POP7, S100P, SNRPA, SORD, STOML2, UMPS, and a housekeeping gene; (b) normalizing the expression level of each of ADRM1, CDK4, COMT, DHCR7, HMOX2, MCM2, PDXK, POP7, S100P, SNRPA, SORD, STOML2, and UMPS to the expression level of the housekeeping gene, thereby obtaining a normalized expression level of each of ADRM1, CDK4, COMT, DHCR7, HMOX2, MCM2, PDXK, POP7
  • the present disclosure provides a method for detecting a colon cancer in a subject in need thereof, the method comprising: (a) determining the expression level of at least 14 biomarkers from a test sample from the subject by contacting the test sample with a plurality of agents specific to detect the expression of the at least 14 biomarkers, wherein the 14 biomarkers comprise ADRM1, CDK4, COMT, DHCR7, HMOX2, MCM2, PDXK, POP7, S100P, SNRPA, SORD, STOML2, UMPS, and a housekeeping gene; (b) normalizing the expression level of each of ADRM1, CDK4, COMT, DHCR7, HMOX2, MCM2, PDXK, POP7, S100P, SNRPA, SORD, STOML2, and UMPS to the expression level of the housekeeping gene, thereby obtaining a normalized expression level of each of ADRM41, CDK4, COMT, DHCR7, HMOX2, MCM2, PDXK,
  • the present disclosure provides a method for determining whether a colon cancer in a subject is stable or progressive, the method comprising: (a) determining the expression level of at least 14 biomarkers from a test sample from the subject by contacting the test sample with a plurality of agents specific to detect the expression of the at least 14 biomarkers, wherein the 14 biomarkers comprise ADRM1, CDK4, COMT, DHCR7, HMOX2, MCM2, PDXK, POP7, S100P, SNRPA, SORD, STOML2, UMPS, and a housekeeping gene; (b) normalizing the expression level of each of ADRM1, CDK4, COMT, DHCR7, HMOX2, MCM2, PDXK, POP7, S100P, SNRPA, SORD, STOML2, and UMPS to the expression level of the housekeeping gene, thereby obtaining a normalized expression level of each of ADM1, CDK4, COMT, DHCR7, HMOX2, MCM2, PDXK
  • the present disclosure provides a method for determining whether a colon cancer in a subject is stable or progressive, the method comprising: (a) determining the expression level of at least 14 biomarkers from a test sample from the subject by contacting the test sample with a plurality of agents specific to detect the expression of the at least 14 biomarkers, wherein the 14 biomarkers comprise ADRM1, CDK4, COMT, DHCR7, HMOX2, MCM2, PDXK, POP7, S100P, SNRPA, SORD, STOML2, UMPS, and a housekeeping gene; (b) normalizing the expression level of each of ADRM1, CDK4, COMT, DHCR7, HMOX2, MCM2, PDXK, POP7, S100P, SNRPA, SORD, STOML2, and UMPS to the expression level of the housekeeping gene, thereby obtaining a normalized expression level of each of ADM1, CDK4, COMT, DHCR7, HMOX2, MCM2, PDXK
  • a method for determining the completeness of surgery in a subject having a colon cancer comprising: (a) determining the expression level of at least 14 biomarkers from a test sample from the subject after the surgery by contacting the test sample with a plurality of agents specific to detect the expression of the at least 14 biomarkers, wherein the 14 biomarkers comprise ADRM1, CDK4, COMT, DHCR7, HMOX2, MCM2, PDXK, POP7, S100P, SNRPA, SORD, STOML2, UMPS, and a housekeeping gene; (b) normalizing the expression level of each of ADRM1, CDK4, COMT, DHCR7, HMOX2, MCM2, PDXK, POP7, S100P, SNRPA, SORD, STOML2, and UMPS to the expression level of the housekeeping gene, thereby obtaining a normalized expression level of each of ADRM1, CDK4, COMT, DHCR7, HMOX2, MCM2, PDXK
  • the present disclosure provides a method for determining the completeness of surgery in a subject having a colon cancer, the method comprising: (a) determining the expression level of at least 14 biomarkers from a test sample from the subject after the surgery by contacting the test sample with a plurality of agents specific to detect the expression of the at least 14 biomarkers, wherein the 14 biomarkers comprise ADRM1, CDK4, COMT, DHCR7, HMOX2, MCM2, PDXK, POP7, S100P, SNRPA, SORD, STOML2, UMPS, and a housekeeping gene; (b) normalizing the expression level of each of ADRM1, CDK4, COMT, DHCR7, HMOX2, MCM2, PDXK, POP7, S100P, SNRPA, SORD, STOML2, and UMPS to the expression level of the housekeeping gene, thereby obtaining a normalized expression level of each of ADRM1, CDK4, COMT, DHCR7, HMOX2, MCM2,
  • the present disclosure provides a method comprising: (a) determining the expression level of at least 14 biomarkers from a test sample from a subject by contacting the test sample with a plurality of agents specific to detect the expression of the at least 14 biomarkers, wherein the 14 biomarkers comprise ADRM1, CDK4, COMT, DHCR7, HMOX2, MCM2, PDXK, POP7, S100P, SNRPA, SORD, STOML2, UMPS, and a housekeeping gene; (b) normalizing the expression level of each of ADRM1, CDK4, COMT, DHCR7, HMOX2, MCM2, PDXK, POP7, S100P, SNRPA, SORD, STOML2, and UMPS to the expression level of the housekeeping gene, thereby obtaining a normalized expression level of each of ADM1, CDK4, COMT, DHCR7, HMOX2, MCM2, PDXK, POP7, S100P, SNRPA, SORD, STOML2, and
  • the present disclosure provides a method for evaluating the response of a subject having a colon cancer to a first therapy, the method comprising: (1) at a first time point: (a) determining the expression level of at least 14 biomarkers from a first test sample from the subject by contacting the first test sample with a plurality of agents specific to detect the expression of the at least 14 biomarkers, wherein the 14 biomarkers comprise ADM1, CDK4, COMT, DHCR7, HMOX2, MCM2, PDXK, POP7, S100P, SNRPA, SORD, STOML2, UMPS, and a housekeeping gene; (b) normalizing the expression level of each of ADM1, CDK4, COMT, DHCR7, HMOX2, MCM2, PDXK, POP7, S100P, SNRPA, SORD, STOML2, and UMPS to the expression level of the housekeeping gene, thereby obtaining a normalized expression level of each of ADRM1, CDK4, COMT, DHCR
  • the present disclosure provides a method for evaluating the response of a subject having a colon cancer to a therapy, the method comprising: (1) at a first time point, performing the following steps that include (a) determining the expression level of at least 14 biomarkers from a first test sample from the subject by contacting the first test sample with a plurality of agents specific to detect the expression of the at least 14 biomarkers, wherein the 14 biomarkers comprise ADRM1, CDK4, COMT, DHCR7, HMOX2, MCM2, PDXK, POP7, S100P, SNRPA, SORD, STOML2, UMPS, and a housekeeping gene; (b) normalizing the expression level of each of ADRM1, CDK4, COMT, DHCR7, HMOX2, MCM2, PDXK, POP7, S100P, SNRPA, SORD, STOML2, and UMPS to the expression level of the housekeeping gene, thereby obtaining a normalized expression level of each of ADM1, CDK4, CO
  • a method of the present disclosure can further comprise continuing to administer a first therapy to a subject when a second score is significantly decreased as compared to a first score.
  • a method of the present disclosure can further comprise discontinuing administration of a first therapy to a subject when a second score is not significantly decreased as compared to a first score.
  • a method of the present disclosure can further comprise administering a second therapy to a subject when a second score is not significantly decreased as compared to a first score.
  • a second score is significantly decreased as compared to a first score when the second score is at least 25% less than the first score.
  • a predetermined cutoff value can be 50% on a scale of 0-100%.
  • a predetermined cutoff value can be 60% on a scale of 0-100%.
  • a housekeeping gene can be selected from the group consisting of MRPL19, PSMC4, SF3A1, PUM1, ACTB, GAPD, GUSB, RPLP0, TFRC, MORF4L1, 18S, PPIA, PGK1, RPL13A, B2M, YWHAZ, SDHA, and HPRT1.
  • the housekeeping gene can be MORF4L1.
  • a method of the present disclosure can have a sensitivity greater than 85%. In some aspects, a method of the present disclosure can have a specificity of greater than 85%.
  • a biomarker can comprise RNA, cDNA, protein or any combination thereof.
  • the RNA can be reverse transcribed to produce cDNA, and the produced cDNA expression level can be detected.
  • a biomarker or the expression of a biomarker can be detected by forming a complex between the biomarker and a labeled probe or primer.
  • the protein when a biomarker is protein, the protein can be detected by forming a complex between the protein and a labeled antibody.
  • the RNA or cDNA when a biomarker is RNA or cDNA, can be detected by forming a complex between the RNA or cDNA and a labeled nucleic acid probe or primer.
  • a complex between the RNA or cDNA and the labeled nucleic acid probe or primer can be a hybridization complex.
  • a predetermined cutoff value can be derived from a plurality of reference samples obtained from subjects not having or not diagnosed with a neoplastic disease.
  • the neoplastic disease can be colon cancer.
  • an algorithm can be XGBoost (XGB), Random Forest (RF), glmnet, cforest, Classification and Regression Trees for Machine Learning (CART), treebag, K-Nearest Neighbors (kNN), neural network (nnet), Support Vector Machine radial (SVM-radial), Support Vector Machine linear (SVM-linear), Na ⁇ ve Bayes (NB), multilayer perceptron (mlp) or any combination thereof.
  • XGBoost XGB
  • Random Forest RF
  • glmnet Random Forest
  • CART Classification and Regression Trees for Machine Learning
  • kNN K-Nearest Neighbors
  • neural network nnet
  • SVM-radial Support Vector Machine radial
  • SVM-linear Support Vector Machine linear
  • NB Na ⁇ ve Bayes
  • mlp multilayer perceptron
  • the methods of the present disclosure can further comprise administering to a subject a first therapy when a score is equal to or greater than a predetermined cutoff.
  • a first time point can be prior to the administration of a first therapy to the subject.
  • a first time point can be after the administration of the first therapy to the subject.
  • a therapy can comprise anti-cancer therapy, surgery, chemotherapy, targeted drug therapy, radiation therapy, immunotherapy or any combination thereof.
  • surgery can comprise removing a polyp during a colonoscopy, endoscopic mucosal resection, a partial colectomy, an ostomy, removing at least one cancerous lesion from the liver, or any combination thereof.
  • chemotherapy can comprise FOLFOX, FOLFIRI, a combination of 5-FU and leucovorin, capecitabine, irinotecan, CapeOx or any combination thereof.
  • targeted drug therapy can comprise bevacizumab, cetuximab, panitumumab, regorafenib, a combination of trifluridine and tipiracil, a EGFR TKI inhibitor or any combination thereof.
  • anti-cancer therapy can comprise anti-colon cancer therapy.
  • immunotherapy can comprise pembrolizumab, nivolumab or a combination of pembrolizumab and nivolumab.
  • a test sample can be blood, serum, plasma, neoplastic tissue or any combination thereof.
  • a reference sample can be blood, serum, plasma, non-neoplastic tissue or any combination thereof.
  • FIGS. 1 A- 1 B are graphs showing normalized gene expression of the 13 gene signature in colon mucosa ( FIG. 1 A ) and cell lines ( FIG. 1 B ).
  • Levels were ⁇ 20-fold elevated in colon cancer tumor tissue than in normal mucosa. All genes were expressed in three different colon cancer cell lines. Levels were ⁇ 1000 ⁇ elevated compared to normal mucosa. Horizontal lines identify median normalized expression of the 13 genes.
  • FIGS. 2 A- 2 B are graphs showing receiver operator curve analysis of the test set ( FIG. 2 A ) and independent set ( FIG. 2 B ).
  • Each cohort included 136 cancers and 60 controls.
  • the AUROC in the test set was 0.9 and the Youden J index was 0.71.
  • the AUROC was 0.86 with a Youden index of 0.6.
  • Z-statistics ranged 11.2-15.6 and were highly significant (p ⁇ 0.0001).
  • the sensitivity and specificity of the test ranged 85-87.5% and 75-83%, respectively.
  • the AUROC was 0.88, p ⁇ 0.0001 ( FIG. 3 B ).
  • Horizontal lines identify median expression of the normalized 13 gene signature (ColoTest).
  • FIGS. 4 A- 4 B are graphs showing decision curve analysis ( FIG. 4 A ) and risk analysis ( FIG. 4 B ) for the ColoTest. This exhibited >50% standardized predictive benefit up to a risk threshold of 80%.
  • the probit risk assessment plot identified a ColoTest score >50% was 75% accurate for predicting colon cancer in a blood sample. This was increased to >80% at a ColoTest score >60%.
  • FIGS. 6 A- 6 C are graphs showing ColoTest scores in stable and progressive disease. Test scores were not significantly different between those identified as stable and those with progressive disease at the time of assessment ( FIG. 6 A ). Of the 17 with stable disease, 12 exhibited disease progression in the 3 month follow-up. Levels in those who truly had demonstrable stable disease were low (16 ⁇ 10%) ( FIG. 6 B ). In those who did progress in the 3 months levels were not different to those that had progressive disease (73 ⁇ 16% vs. 68 ⁇ 25%). The AUROC for differentiating stable from progressing/progressive disease was 0.97, p ⁇ 0.0001 ( FIG. 6 C ).
  • FIG. 7 is a graph showing comparison of AUROC between the ColoTest and CEA for differentiating stable from progressive disease.
  • FIG. 8 is a graph showing the effect of treatment on the ColoTest. Levels prior to treatment are elevated (82 ⁇ 9%). In those who responded to therapy with disease stabilization, levels were reduced to 14 ⁇ 7% (*p ⁇ 0.0001). In those that exhibited disease progression because of treatment failure, levels were elevated (69 ⁇ 21%).
  • Colon cancer is cancer of the large intestine (colon). Symptoms of colon cancer include, but are not limited to: (a) a change in bowel habits, (b) rectal bleeding or blood in the stool, (c) persistent abdominal discomfort, such as cramps, gas or pain, (d) a feeling that the bowel doesn't empty completely, (e) weakness or fatigue, and (f) unexplained weight loss.
  • Described herein are methods to quantitate (score) the circulating colon cancer molecular signature with high sensitivity and specificity for purposes including, but not limited to, detecting a colon cancer, determining whether a colon cancer is stable or progressive, determining the completeness of surgery, and evaluating the response to a colon cancer therapy.
  • the present invention is based on the discovery that the expression levels of ADRM1, CDK4, COMT, DHCR7, HMOX2, MCM2, PDXK, POP7, S100P, SNRPA, SORD, STOML2, and UMPS, normalized by the expression level of a housekeeping gene such as MORF4L1, are elevated in subjects having colon cancers as compared to healthy subjects.
  • the present disclosure provides a method for detecting a colon cancer in a subject in need thereof, the method comprising: (a) determining the expression level of at least 14 biomarkers from a test sample from the subject by contacting the test sample with a plurality of agents specific to detect the expression of the at least 14 biomarkers, wherein the 14 biomarkers comprise ADRM1, CDK4, COMT, DHCR7, HMOX2, MCM2, PDXK, POP7, S100P, SNRPA, SORD, STOML2, UMPS, and a housekeeping gene; (b) normalizing the expression level of each of ADRM1, CDK4, COMT, DHCR7, HMOX2, MCM2, PDXK, POP7, S100P, SNRPA, SORD, STOML2, and UMPS to the expression level of the housekeeping gene, thereby obtaining a normalized expression level of each of ADRM1, CDK4, COMT, DHCR7, HMOX2, MCM2, PDXK, POP
  • step (e) can comprise producing a report, wherein the report identifies the presence of a colon cancer in the subject when the score is equal to or greater than the first predetermined cutoff value or identifies the absence of a colon cancer in the subject when the score is less than the first predetermined cutoff value.
  • the preceding method can further comprise administering to the subject a first therapy.
  • the preceding method can further comprise administering to the subject a first therapy when the score is equal to or greater than the predetermined cutoff.
  • the present disclosure also provides a method for determining whether a colon cancer in a subject is stable or progressive, the method comprising: (a) determining the expression level of at least 14 biomarkers from a test sample from the subject by contacting the test sample with a plurality of agents specific to detect the expression of the at least 14 biomarkers, wherein the 14 biomarkers comprise ADRM1, CDK4, COMT, DHCR7, HMOX2, MCM2, PDXK, POP7, S100P, SNRPA, SORD, STOML2, UMPS, and a housekeeping gene; (b) normalizing the expression level of each of ADRM1, CDK4, COMT, DHCR7, HMOX2, MCM2, PDXK, POP7, S100P, SNRPA, SORD, STOML2, and UMPS to the expression level of the housekeeping gene, thereby obtaining a normalized expression level of each of ADRM1, CDK4, COMT, DHCR7, HMOX2, MCM2, PDXK, P
  • step (e) can comprise producing a report, wherein the report identifies that the colon cancer is progressive when the score is equal to or greater than the second predetermined cutoff value or identifies that the colon cancer is stable when the score is less than the second predetermined cutoff value.
  • the preceding method can further comprise administering to the subject a first therapy.
  • the preceding method can further comprise administering to the subject a first therapy when the score is equal to or greater than the predetermined cutoff.
  • the method further comprises treating the subject with a progressive colon cancer with surgery, chemotherapy, targeted drug therapy, radiation therapy, immunotherapy, or a combination thereof.
  • the present disclosure also provides a method for determining the completeness of surgery in a subject having a colon cancer, the method comprising: (a) determining the expression level of at least 14 biomarkers from a test sample from the subject after the surgery by contacting the test sample with a plurality of agents specific to detect the expression of the at least 14 biomarkers, wherein the 14 biomarkers comprise ADM1, CDK4, COMT, DHCR7, HMOX2, MCM2, PDXK, POP7, S100P, SNRPA, SORD, STOML2, UMPS, and a housekeeping gene; (b) normalizing the expression level of each of ADRM1, CDK4, COMT, DHCR7, HMOX2, MCM2, PDXK, POP7, S100P, SNRPA, SORD, STOML2, and UMPS to the expression level of the housekeeping gene, thereby obtaining a normalized expression level of each of ADRM1, CDK4, COMT, DHCR7, HMOX2, MCM2, PD
  • step (e) can comprise producing a report, wherein the report identifies that the colon cancer is not completely removed when the score is equal to or greater than the first predetermined cutoff value or identifies that the colon cancer is completely removed when the score is less than the first predetermined cutoff value.
  • the preceding method can further comprise administering to the subject a first therapy.
  • the preceding method can further comprise administering to the subject a first therapy when the score is equal to or greater than the predetermined cutoff.
  • the present disclosure also provides a method comprising: (a) determining the expression level of at least 14 biomarkers from a test sample from a subject by contacting the test sample with a plurality of agents specific to detect the expression of the at least 14 biomarkers, wherein the 14 biomarkers comprise ADM1, CDK4, COMT, DHCR7, HMOX2, MCM2, PDXK, POP7, S100P, SNRPA, SORD, STOML2, UMPS, and a housekeeping gene; (b) normalizing the expression level of each of ADRM1, CDK4, COMT, DHCR7, HMOX2, MCM2, PDXK, POP7, S100P, SNRPA, SORD, STOML2, and UMPS to the expression level of the housekeeping gene, thereby obtaining a normalized expression level of each of ADRM1, CDK4, COMT, DHCR7, HMOX2, MCM2, PDXK, POP7, S100P, SNRPA, SORD, STOML2,
  • the response of a subject having a colon cancer to a therapy can also be evaluated by comparing the scores determined by the same algorithm at different time points of the therapy.
  • the first time point can be prior to or after the administration of the therapy to the subject; the second time point is after the first time point and after the administration of the therapy to the subject.
  • a first score is generated at the first time point, and a second score is generated at the second time point.
  • the second score is significantly decreased as compared to the first score, the subject is considered to be responsive to the therapy.
  • the present disclosure provides a method for evaluating the response of a subject having a colon cancer to a first therapy, the method comprising: (1) at a first time point: (a) determining the expression level of at least 14 biomarkers from a first test sample from the subject by contacting the first test sample with a plurality of agents specific to detect the expression of the at least 14 biomarkers, wherein the 14 biomarkers comprise ADRM1, CDK4, COMT, DHCR7, HMOX2, MCM2, PDXK, POP7, S100P, SNRPA, SORD, STOML2, UMPS, and a housekeeping gene; (b) normalizing the expression level of each of ADRM1, CDK4, COMT, DHCR7, HMOX2, MCM2, PDXK, POP7, S100P, SNRPA, SORD, STOML2, and UMPS to the expression level of the housekeeping gene, thereby obtaining a normalized expression level of each of ADRM1, CDK4, COMT, DHCR7
  • step (4) can comprise producing a report, wherein the report identifies that the subject is responsive to the first therapy when the second score is significantly decreased as compared to the first score or identifies that the subject is not responsive to the first therapy when the second score is not significantly decreased as compared to the first score.
  • the second score is significantly decreased as compared to the first score when the second score is at least about 10% less than the first score, or at least about 20% less than the first score, or at least about 25% less than the first score, at least about 40% less than the first score, at least about 50% less than the first score, or at least about 60% less than the first score, or at least about 70% less than the first score, or at least about 75% less than the first score, or at least about 80% less than the first score, or at least about 90% less than the first score, or at least about 95% less than the first score or at least about 95% less than the first score.
  • the subject is considered to be not responsive to the therapy.
  • a first time point can be prior to the administration of a first therapy to the subject.
  • a first time point can be after the administration of a first therapy to the subject.
  • the preceding method can further comprise continuing to administer the first therapy to the subject when the second score is significantly decreased as compared to the first score.
  • the preceding method can further comprise discontinuing administration of the first therapy to the subject when the second score is not significantly decreased as compared to the first score.
  • the preceding method can further comprise administering a second therapy to the subject when the second score is not significantly decreased as compared to the first score.
  • a predetermined cutoff value can be about 50% on a scale of 0-100%.
  • a predetermined cutoff value can be about 60% on a scale of 0-100%.
  • a predetermine cutoff value can be about 10%, or about 20%, or about 30%, or about 40%, or about 70%, or about 80%, or about 90% on a scale of 0-100%.
  • a test sample can be any biological fluid obtained from the subject.
  • a test sample can be blood, serum, plasma, neoplastic tissue or any combination thereof.
  • the test sample is blood.
  • the test sample is serum.
  • the test sample is plasma.
  • a housekeeping gene can comprise, but is not limited to, MRPL19, PSMC4, SF3A1, PUM1, ACTB, GAPD, GUSB, RPLP0, TFRC, MORF4L1, 18S, PPIA, PGK1, RPL13A, B2M, YWHAZ, SDHA, and HPRT1.
  • the housekeeping gene is MORF4L1.
  • the methods of the present disclosure can have a sensitivity of at least about 50%, or at least about 60%, or at least about 70%, or at least about 75%, or at least about 80%, or at least about 85%, or at least about 90%, or at least about 95%, or at least about 99%.
  • the methods of the present disclosure can have a sensitivity of greater than about 50%, or greater than about 60%, or greater than about 70%, or greater than about 75%, or greater than about 80%, or greater than about 85%, or greater than about 90%, or greater than about 95%, or greater than about 99%.
  • the methods of the present disclosure can have a specificity of at least about 50%, or at least about 60%, or at least about 70%, or at least about 75%, or at least about 80%, or at least about 85%, or at least about 90%, or at least about 95%, or at least about 99%.
  • the methods of the present disclosure can have a specificity of greater than about 50%, or greater than about 60%, or greater than about 70%, or greater than about 75%, or greater than about 80%, or greater than about 85%, or greater than about 90%, or greater than about 95%, or greater than about 99%.
  • the methods of the present disclosure can have an accuracy of at least about 50%, or at least about 60%, or at least about 70%, or at least about 75%, or at least about 80%, or at least about 85%, or at least about 90%, or at least about 95%, or at least about 99%.
  • the methods of the present disclosure can have an accuracy of greater than about 50%, or greater than about 60%, or greater than about 70%, or greater than about 75%, or greater than about 80%, or greater than about 85%, or greater than about 90%, or greater than about 95%, or greater than about 99%.
  • a predetermined cutoff value can be derived from a plurality of reference samples obtained from subjects not having or not diagnosed with a neoplastic disease.
  • the neoplastic disease can be colon cancer.
  • the plurality of reference samples can comprise about 2-500, 2-200, 10-100, or 20-80 reference samples. Each reference sample produces a score using the algorithm, and the first predetermined cutoff value can be an arithmetic mean of these scores.
  • Each reference sample can be blood, serum, plasma, or non-neoplastic tissue. In some aspects, each reference sample is blood. In some aspects, each reference sample is of the same type as the test sample.
  • Each of the biomarkers disclosed herein may have one or more transcript variants.
  • the methods disclosed herein can measure the expression level of any one of the transcript variants for each biomarker.
  • the expression level can be measured in a number of ways, including, but not limited to: measuring the mRNA encoded by the selected genes; measuring the amount of protein encoded by the selected genes; and measuring the activity of the protein encoded by the selected genes.
  • a biomarker can be RNA, cDNA, protein or any combination thereof.
  • the biomarker is RNA
  • the RNA can be reverse transcribed to produce cDNA (such as by RT-PCR), and the produced cDNA expression level can be detected.
  • the expression level of a biomarker can be detected by forming a complex between the biomarker and a labeled probe or primer.
  • the biomarker is RNA or cDNA
  • the RNA or cDNA can be detected by forming a complex between the RNA or cDNA and a labeled nucleic acid probe or primer.
  • the complex between the RNA or cDNA and the labeled nucleic acid probe or primer can be a hybridization complex.
  • gene expression can be detected by microarray analysis. Differential gene expression can also be identified, or confirmed using the microarray technique. Thus, the expression profile biomarkers can be measured in either fresh or fixed tissue, using microarray technology.
  • polynucleotide sequences of interest including cDNAs and oligonucleotides
  • the arrayed sequences are then hybridized with specific DNA probes from cells or tissues of interest.
  • the source of mRNA typically is total RNA isolated from a biological sample, and corresponding normal tissues or cell lines may be used to determine differential expression.
  • PCR amplified inserts of cDNA clones are applied to a substrate in a dense array.
  • at least 10,000 nucleotide sequences are applied to the substrate.
  • the microarrayed genes, immobilized on the microchip at 10,000 elements each, are suitable for hybridization under stringent conditions.
  • Fluorescently labeled cDNA probes may be generated through incorporation of fluorescent nucleotides by reverse transcription of RNA extracted from tissues of interest. Labeled cDNA probes applied to the chip hybridize with specificity to each spot of DNA on the array.
  • the microarray chip is scanned by a device such as, confocal laser microscopy or by another detection method, such as a CCD camera. Quantitation of hybridization of each arrayed element allows for assessment of corresponding mRNA abundance. With dual color fluorescence, separately labeled cDNA probes generated from two sources of RNA are hybridized pair-wise to the array. The relative abundance of the transcripts from the two sources corresponding to each specified gene is thus determined simultaneously. Microarray analysis can be performed by commercially available equipment, following manufacturer's protocols.
  • the biomarkers can be detected in a biological sample using qRT-PCR.
  • the first step in gene expression profiling by RT-PCR is extracting RNA from a biological sample followed by the reverse transcription of the RNA template into cDNA and amplification by a PCR reaction.
  • the reverse transcription reaction step is generally primed using specific primers, random hexamers, or oligo-dT primers, depending on the goal of expression profiling.
  • the two commonly used reverse transcriptases are avilo myeloblastosis virus reverse transcriptase (AMV-RT) and Moloney murine leukemia virus reverse transcriptase (MLV-RT).
  • the protein when the biomarker is a protein, the protein can be detected by forming a complex between the protein and a labeled antibody.
  • the label can be any label for example a fluorescent label, chemiluminescence label, radioactive label, etc.
  • Exemplary methods for protein detection include, but are not limited to, enzyme immunoassay (EIA), radioimmunoassay (MA), Western blot analysis and enzyme linked immunoabsorbant assay (ELISA).
  • EIA enzyme immunoassay
  • MA radioimmunoassay
  • ELISA enzyme linked immunoabsorbant assay
  • the biomarker can be detected in an ELISA, in which the biomarker antibody is bound to a solid phase and an enzyme-antibody conjugate is employed to detect and/or quantify biomarker present in a sample.
  • a western blot assay can be used in which solubilized and separated biomarker is bound to nitrocellulose paper. The combination of a highly specific, stable liquid conjugate with
  • the methods described herein can have a specificity, sensitivity, and/or accuracy of at least 75%, 80%, 85%, 90%, 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, or 99%.
  • a labeled probe, a labeled primer, a labeled antibody or a labeled nucleic acid can comprise a fluorescent label.
  • the algorithm analyzes the data (i.e., expression levels) and then assigns a score.
  • the algorithm can be a machine-learning algorithm.
  • Exemplary algorithms that can be used in the methods disclosed herein can include, but are not limited to, XGBoost (XGB), Random Forest (RF), glmnet, cforest, Classification and Regression Trees for Machine Learning (CART), treebag, K-Nearest Neighbors (kNN), neural network (nnet), Support Vector Machine radial (SVM-radial), Support Vector Machine linear (SVM-linear), Na ⁇ ve Bayes (NB), multilayer perceptron (mlp) or any combination thereof.
  • XGBoost XGB
  • Random Forest RF
  • glmnet Random Forest
  • CART Classification and Regression Trees for Machine Learning
  • kNN K-Nearest Neighbors
  • neural network nnet
  • SVM-radial Support Vector Machine radial
  • SVM-linear Support Vector Machine linear
  • NB Na ⁇ ve Bayes
  • mlp multilayer perceptron
  • the algorithm can be XGB (also called XGBoost).
  • XGB is an implementation of gradient boosted decision trees designed for speed and performance.
  • a therapy can comprise anti-cancer therapy, surgery, chemotherapy, targeted drug therapy, radiation therapy, immunotherapy, or any combination thereof.
  • surgery can comprise removing a polyp during a colonoscopy, endoscopic mucosal resection, a partial colectomy, an ostomy, removing at least one cancerous lesion from the liver, or any combination thereof.
  • anti-cancer therapy can comprise anti-colon cancer therapy.
  • chemotherapy can comprise FOLFOX, FOLFIRI, a combination of 5-FU and leucovorin, capecitabine, irinotecan, CapeOx or any combination thereof.
  • targeted drug therapy can comprise bevacizumab, cetuximab, panitumumab, regorafenib, a combination of trifluridine and tipiracil, an EGFR TKI inhibitor or any combination thereof.
  • immunotherapy can comprise pembrolizumab, nivolumab or a combination of pembrolizumab and nivolumab.
  • a minimally invasive approach to surgery can be used to remove the cancer.
  • the polyp can be removed during a colonoscopy.
  • Endoscopic mucosal resection can be performed to remove larger polyps.
  • Polyps that cannot be removed during a colonoscopy may be removed using laparoscopic surgery.
  • partial colectomy can be performed to remove the part of the colon that contains the cancer, along with a margin of normal tissue on either side of the cancer.
  • an ostomy can be performed to create an opening in the wall of the abdomen from a portion of the remaining bowel for the elimination of stool into a bag that fits securely over the opening. Lymph node removal can also be performed.
  • an operation to relieve a blockage of the colon or other conditions can also be performed.
  • surgery to remove the cancerous lesion from the liver can be performed.
  • chemotherapies either the FOLFOX (5-FU, leucovorin, and oxaliplatin) or CapeOx (capecitabine and oxaliplatin) regimens are used most often, but some patients may get 5-FU with leucovorin or capecitabine alone based on their age and health needs.
  • Irinotecan can also be used as a chemotherapeutic agent for treating a colon cancer.
  • Targeted drug therapies target specific malfunctions that allow cancer cells to grow. These therapies include, but are not limited to, bevacizumab, cetuximab, panitumumab, ramucirumab, regorafenib, ziv-aflibercept, a combination of trifluridine and tipiracil, and an EGFR TKI inhibitor.
  • Immunotherapies for colon cancer include, but are not limited to, pembrolizumab (Keytruda®) and nivolumab (Opdivo®).
  • the sequence information of the colon cancer biomarkers and housekeepers is shown in Table 1.
  • an element means one element or more than one element.
  • nucleic acid molecule As used herein, the terms “polynucleotide” and “nucleic acid molecule” are used interchangeably to mean a polymeric form of nucleotides of at least 10 bases or base pairs in length, either ribonucleotides or deoxynucleotides or a modified form of either type of nucleotide, and is meant to include single and double stranded forms of DNA.
  • a nucleic acid molecule or nucleic acid sequence that serves as a probe in a microarray analysis preferably comprises a chain of nucleotides, more preferably DNA and/or RNA.
  • nucleic acid molecule or nucleic acid sequence comprises other kinds of nucleic acid structures such a for instance a DNA/RNA helix, peptide nucleic acid (PNA), locked nucleic acid (LNA) and/or a ribozyme.
  • PNA peptide nucleic acid
  • LNA locked nucleic acid
  • nucleic acid molecule also encompasses a chain comprising non-natural nucleotides, modified nucleotides and/or non-nucleotide building blocks which exhibit the same function as natural nucleotides.
  • hybridize As used herein, the terms “hybridize,” “hybridizing”, “hybridizes,” and the like, used in the context of polynucleotides, are meant to refer to conventional hybridization conditions, such as hybridization in 50% formamide/6 ⁇ SSC/0.1% SDS/100 ⁇ g/ml ssDNA, in which temperatures for hybridization are above 37 degrees centigrade and temperatures for washing in 0.1 ⁇ SSC/0.1% SDS are above 55 degrees C., and preferably to stringent hybridization conditions.
  • normalization refers to the expression of a differential value in terms of a standard value to adjust for effects which arise from technical variation due to sample handling, sample preparation, and measurement methods rather than biological variation of biomarker concentration in a sample.
  • the absolute value for the expression of the protein can be expressed in terms of an absolute value for the expression of a standard protein that is substantially constant in expression.
  • diagnosis also encompass the terms “prognosis” and “prognostics”, respectively, as well as the applications of such procedures over two or more time points to monitor the diagnosis and/or prognosis over time, and statistical modeling based thereupon.
  • diagnosis includes: a. prediction (determining if a patient will likely develop aggressive disease (hyperproliferative/invasive)), b. prognosis (predicting whether a patient will likely have a better or worse outcome at a pre-selected time in the future), c. therapy selection, d. therapeutic drug monitoring, and e. relapse monitoring.
  • “Accuracy” refers to the degree of conformity of a measured or calculated quantity (a test reported value) to its actual (or true) value. Clinical accuracy relates to the proportion of true outcomes (true positives (TP) or true negatives (TN)) versus misclassified outcomes (false positives (FP) or false negatives (FN)), and may be stated as a sensitivity, specificity, positive predictive values (PPV) or negative predictive values (NPV), or as a likelihood, odds ratio, among other measures.
  • biological sample refers to any sample of biological origin potentially containing one or more biomarkers.
  • biological samples include tissue, organs, or bodily fluids such as whole blood, plasma, serum, tissue, lavage or any other specimen used for detection of disease.
  • a subject refers to a mammal, preferably a human.
  • a subject can have at least one colon cancer symptom.
  • a subject can have a predisposition or familial history for developing a colon cancer.
  • a subject can also have been previously diagnosed with a colon cancer and is tested for cancer recurrence.
  • Treating” or “treatment” as used herein with regard to a condition may refer to preventing the condition, slowing the onset or rate of development of the condition, reducing the risk of developing the condition, preventing or delaying the development of symptoms associated with the condition, reducing or ending symptoms associated with the condition, generating a complete or partial regression of the condition, or some combination thereof.
  • Biomarker levels may change due to treatment of the disease.
  • the changes in biomarker levels may be measured by the present disclosure. Changes in biomarker levels may be used to monitor the progression of disease or therapy.
  • “Altered”, “changed” or “significantly different” refer to a detectable change or difference from a reasonably comparable state, profile, measurement, or the like. Such changes may be all or none. They may be incremental and need not be linear. They may be by orders of magnitude. A change may be an increase or decrease by 5%, 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, 90%, 95%, 99%, 100%, or more, or any value in between 0% and 100%. Alternatively, the change may be 1-fold, 1.5-fold, 2-fold, 3-fold, 4-fold, 5-fold or more, or any values in between 1-fold and five-fold. The change may be statistically significant with a p value of 0.1, 0.05, 0.001, or 0.0001.
  • stable disease refers to a diagnosis for the presence of a colon cancer, however the colon cancer has been treated and remains in a stable condition, i.e. one that that is not progressive, as determined by imaging data and/or best clinical judgment.
  • progressive disease refers to a diagnosis for the presence of a highly active state of a colon cancer, i.e. one has not been treated and is not stable or has been treated and has not responded to therapy, or has been treated and active disease remains, as determined by imaging data and/or best clinical judgment.
  • neoplastic disease refers to any abnormal growth of cells or tissues being either benign (non-cancerous) or malignant (cancerous).
  • the neoplastic disease can be a colon cancer.
  • Neoplastic tissue refers to a mass of cells that grow abnormally.
  • non-neoplastic tissue refers to a mass of cells that grow normally.
  • immunotherapy can refer to activating immunotherapy or suppressing immunotherapy.
  • activating immunotherapy refers to the use of a therapeutic agent that induces, enhances, or promotes an immune response, including, e.g., a T cell response
  • suppressing immunotherapy refers to the use of a therapeutic agent that interferes with, suppresses, or inhibits an immune response, including, e.g., a T cell response.
  • Activating immunotherapy may comprise the use of checkpoint inhibitors.
  • Activating immunotherapy may comprise administering to a subject a therapeutic agent that activates a stimulatory checkpoint molecule.
  • Stimulatory checkpoint molecules include, but are not limited to, CD27, CD28, CD40, CD122, CD137, OX40, GITR and ICOS.
  • Therapeutic agents that activate a stimulatory checkpoint molecule include, but are not limited to, MEDI0562, TGN1412, CDX-1127, lipocalin.
  • antibody herein is used in the broadest sense and encompasses various antibody structures, including but not limited to monoclonal antibodies, polyclonal antibodies, multispecific antibodies (e.g., bispecific antibodies), and antibody fragments so long as they exhibit the desired antigen-binding activity.
  • An antibody that binds to a target refers to an antibody that is capable of binding the target with sufficient affinity such that the antibody is useful as a diagnostic and/or therapeutic agent in targeting the target.
  • the extent of binding of an anti-target antibody to an unrelated, non-target protein is less than about 10% of the binding of the antibody to target as measured, e.g., by a radioimmunoassay (RIA) or biacore assay.
  • RIA radioimmunoassay
  • an antibody that binds to a target has a dissociation constant (Kd) of ⁇ 1 ⁇ M, ⁇ 100 nM, ⁇ 10 nM, ⁇ 1 nM, ⁇ 0.1 nM, ⁇ 0.01 nM, or ⁇ 0.001 nM (e.g. 108 M or less, e.g. from 108 M to 1013 M, e.g., from 109 M to 1013 M).
  • Kd dissociation constant
  • an anti-target antibody binds to an epitope of a target that is conserved among different species.
  • blocking antibody or an “antagonist antibody” is one that partially or fully blocks, inhibits, interferes, or neutralizes a normal biological activity of the antigen it binds.
  • an antagonist antibody may block signaling through an immune cell receptor (e.g., a T cell receptor) so as to restore a functional response by T cells (e.g., proliferation, cytokine production, target cell killing) from a dysfunctional state to antigen stimulation.
  • an immune cell receptor e.g., a T cell receptor
  • an “agonist antibody” or “activating antibody” is one that mimics, promotes, stimulates, or enhances a normal biological activity of the antigen it binds.
  • Agonist antibodies can also enhance or initiate signaling by the antigen to which it binds.
  • agonist antibodies cause or activate signaling without the presence of the natural ligand.
  • an agonist antibody may increase memory T cell proliferation, increase cytokine production by memory T cells, inhibit regulatory T cell function, and/or inhibit regulatory T cell suppression of effector T cell function, such as effector T cell proliferation and/or cytokine production.
  • antibody fragment refers to a molecule other than an intact antibody that comprises a portion of an intact antibody that binds the antigen to which the intact antibody binds.
  • antibody fragments include but are not limited to Fv, Fab, Fab′, Fab′-SH, F(ab′)2; diabodies; linear antibodies; single-chain antibody molecules (e.g. scFv); and multispecific antibodies formed from antibody fragments.
  • Administering chemotherapy to a subject can comprise administering a therapeutically effective dose of at least one chemotherapeutic agent.
  • Chemotherapeutic agents include, but are not limited to, 13-cis-Retinoic Acid, 2-CdA, 2-Chlorodeoxyadenosine, 5-Azacitidine, 5-Fluorouracil, 5-FU, 6-Mercaptopurine, 6-MP, 6-TG, 6-Thioguanine, Abemaciclib, Abiraterone acetate, Abraxane, Accutane, Actinomycin-D, Adcetris, Ado-Trastuzumab Emtansine, Adriamycin, Adrucil, Afatinib, Afinitor, Agrylin, Ala-Cort, Aldesleukin, Alemtuzumab, Alecensa, Alectinib, Alimta, Alitretinoin, Alkaban-AQ, Alkeran, All-transretinoic Acid, Alpha Interferon
  • Clinical benefit can be measured by assessing various endpoints, e.g., inhibition, to some extent, of disease progression, including slowing down and complete arrest; reduction in the number of disease episodes and/or symptoms; reduction in lesion size; inhibition (i.e., reduction, slowing down or complete stopping) of disease cell infiltration into adjacent peripheral organs and/or tissues; inhibition (i.e.
  • cancer and “cancerous” refer to or describe the physiological condition in mammals that is typically characterized by unregulated cell growth. Included in this definition are benign and malignant cancers. Examples of cancer include but are not limited to, carcinoma, lymphoma, blastoma, sarcoma, and leukemia.
  • cancers include adrenocortical carcinoma, bladder urothelial carcinoma, breast invasive carcinoma, cervical squamous cell carcinoma, endocervical adenocarcinoma, cholangiocarcinoma, colon adenocarcinoma, lymphoid neoplasm diffuse large B-cell lymphoma, esophageal carcinoma, glioblastoma multiforme, head and neck squamous cell carcinoma, kidney chromophobe, kidney renal clear cell carcinoma, kidney renal papillary cell carcinoma, acute myeloid leukemia, brain lower grade glioma, liver hepatocellular carcinoma, lung adenocarcinoma, lung squamous cell carcinoma, mesothelioma, ovarian serous cystadenocarcinoma, pancreatic adenocarcinoma, pheochromocytoma, paraganglioma, prostate adenocarcinoma, rectum a
  • cancers include breast cancer, lung cancer, lymphoma, melanoma, liver cancer, colorectal cancer, ovarian cancer, bladder cancer, renal cancer or gastric cancer.
  • cancer include neuroendocrine cancer, non-small cell lung cancer (NSCLC), small cell lung cancer, thyroid cancer, endometrial cancer, biliary cancer, esophageal cancer, anal cancer, salivary, cancer, vulvar cancer or cervical cancer.
  • NSCLC non-small cell lung cancer
  • esophageal cancer anal cancer
  • salivary cancer
  • cancer vulvar cancer or cervical cancer.
  • tumor refers to all neoplastic cell growth and proliferation, whether malignant or benign, and all pre-cancerous and cancerous cells and tissues.
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  • Gene co-expression networks were generated to identify temporal patterns of gene regulation associated with colon cancer. A total of 513 nodes with 53,786 links were identified.
  • the dataset was randomly split into training and testing partitions for model creation and validation respectively.
  • Twelve algorithms were evaluated (XGB, RF, glmnet, cforest, CART, treebag, knn, nnet, SVM-radial, SVM-linear, NB and mlp).
  • the top performing algorithm (XGB—“gradient boosting”) best predicted the training data.
  • XGB “gradient boosting”
  • XGB produced probability scores that predicted the sample.
  • Each probability score reflects the “certainty” of an algorithm that an unknown sample belongs to either “Control” or “Colon Cancer” class.
  • the score exhibited an area under the curve (AUC) of 0.90 (training) and 0.86 (test set).
  • the metrics are: sensitivity: 85.3-87.5% and specificity: 75-83.3%.
  • FIGS. 4 A- 4 B A decision curve analysis was used to quantify the clinical benefit of the diagnostic test ( FIGS. 4 A- 4 B ).
  • the ColoTest exhibited >50% standardized predictive benefit up to a risk threshold of 80%.
  • the probit risk assessment plot identified a ColoTest score >50% was 75% accurate for predicting colon cancer in a blood sample. This was increased to >80% at a ColoTest score ⁇ 60%. The tool can therefore accurately differentiate between controls and colon cancer disease.
  • ROC analysis identified the ColoTest had an AUC: 0.97 for differentiating stable from progressive disease.
  • the z-statistic for differentiating controls was 20.6.
  • Further evaluation of this cohort identified that patients who exhibited disease progression despite therapy exhibited higher scores than those responding to therapy ( FIG. 8 ).
  • Therapies included bevacizumab, chemotherapy and EGFR TKI inhibitors. The tool can therefore accurately identify treatment failure in colon cancer disease.

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Abstract

The present invention is directed to methods for detecting a colon cancer, methods for determining whether a colon cancer is stable or progressive, methods for determining a risk for disease relapse, and methods for determining a response by a subject having a colon cancer to a therapy.

Description

CROSS-REFERENCE TO RELATED APPLICATIONS
This application is a divisional of U.S. patent application Ser. No. 16/253,697, filed Jan. 22, 2019, now U.S. Pat. No. 11,414,707, which claims priority to, and the benefit of, U.S. Provisional Application No. 62/620,015, filed Jan. 22, 2018. The contents of each of the aforementioned patent applications are incorporated herein by reference in their entireties.
SEQUENCE LISTING
The Sequence Listing XML associated with this application is provided electronically in XML file format and is hereby incorporated by reference into the specification. The name of the XML file containing the Sequence Listing XML is “LBIO-004_C01US_SeqList.xml”. The XML filed is 112,806 bytes in size, and was created on Jul. 25, 2022, and is being submitted elelctronically via USPTO Patent Center.
FIELD OF THE INVENTION
The present invention relates to colon cancer detection.
BACKGROUND OF THE INVENTION
Colorectal cancer (CRC) is one of the most commonly diagnosed cancers worldwide. In the US, CRC is the second leading cause of death as it is in Europe, after lung cancer. Worldwide, it is the fourth most common cause of cancer death. Although surgical resection followed by chemotherapy is the leading treatment option, approximately half eventually die due to distant metastases. Currently, the 5-year overall survival rate of patients with primary CRC can be up to 90%, but it will be reduced to −50% in patients with advanced non-metastatic tumors, and can be further decreased to <10% in patients in whom the disease is resected at its earliest stages, owing to an incomplete understanding of the molecular mechanisms underpinning its pathogenesis.
Overall survival is associated with the disease stage at the time of diagnosis, suggesting that early detection of disseminated disease is of considerable significance. Consequently, the development of new diagnostic methods that better define disease stage and can better monitor disease progression is critical.
Surveillance remains a cornerstone approach to detect recurrence at an early stage and plan further therapeutic strategies. After potentially curative resection, monitoring can be undertaken through measurement of blood biomarkers and/or imaging like CT to detect asymptomatic metastatic disease earlier. Pooled data from randomized trials published from 1995 to 2016, however, identifies that a benefit from surgical treatment resulting from earlier detection of metastases, does not occur. This likely reflects the poor sensitivity of current biomarkers.
The current biomarker is carcinoembryonic antigen (CEA), a glycoprotein involved in cell adhesion that is not generally expressed in adult tissues except in heavy smokers. Its specialized sialofucosylated glycoforms serve as functional colon carcinoma L-selectin and E-selectin ligands, which may play a role in metastatic dissemination of colon carcinoma cells. CEA is principally used to monitor colorectal carcinoma treatment, to identify recurrences after surgical resection, for staging or to localize cancer spread through measurement of biological fluids. There are, however, significant limitations. While preoperative CEA levels have shown an association with (disease-free) survival, this was chiefly because it was a surrogate for metastatic presentation. Extrapolating the predictive value of preoperative CEA has, however, been shown to be of limited significance for predictions of long-term outcomes in individual cases. This has been independently supported by a prospective analysis, which identified that levels of CEA, and other biomarkers like CA19-9, does not indicate metastasis even at a time-point where clinical signs and imaging techniques has already demonstrated metastasis.
While the molecular basis for the colorectal cancer disease has been well-characterized e.g., microsatellite instability, K-RAS mutations etc., the development of diagnostic and prognostic markers e.g., in urine or stool or as circulating-free DNA that captures this information, remains nascent but have begun to be developed. Examples include measurements of methylation of septin 9, a tumor suppressor involved in cytokinesis during cellular division. This has been used to detect colon cancer; the metrics range between 60-70%. Assessment of circulating free DNA (Line 1 and Alu-based PCR) has a predictive value of 81% with a ROC of 0.86 as a diagnostic, while measurements of circulating tumor cells are also considered useful. TPS (tissue polypeptide specific antigen) can be used as a monitor of colon cancer as can TAG-72 (tumor-associated glycoprotein) but measurements of other single analytes, like CEA or CA19-9, are non-specific.
SUMMARY OF THE INVENTION
Among other things, disclosed herein is a 14-gene expression tool for colon cancer detection.
In one aspect, the present disclosure provides a method for detecting a colon cancer in a subject in need thereof, comprising: (a) determining the expression level of at least 14 biomarkers from a test sample from the subject by contacting the test sample with a plurality of agents specific to detect the expression of the at least 14 biomarkers, wherein the 14 biomarkers comprise ADM1, CDK4, COMT, DHCR7, HMOX2, MCM2, PDXK, POP7, S100P, SNRPA, SORD, STOML2, UMPS, and a housekeeping gene; (b) normalizing the expression level of each of ADRM1, CDK4, COMT, DHCR7, HMOX2, MCM2, PDXK, POP7, S100P, SNRPA, SORD, STOML2, and UMPS to the expression level of the housekeeping gene, thereby obtaining a normalized expression level of each of ADRM1, CDK4, COMT, DHCR7, HMOX2, MCM2, PDXK, POP7, S100P, SNRPA, SORD, STOML2, and UMPS; (c) inputting each normalized expression level into an algorithm to generate a score; (d) comparing the score with a predetermined cutoff value; and (e) identifying the presence of a colon cancer in the subject when the score is equal to or greater than the predetermined cutoff value or identifying the absence of a colon cancer in the subject when the score is less than the predetermined cutoff value.
In one aspect, the present disclosure provides a method for detecting a colon cancer in a subject in need thereof, the method comprising: (a) determining the expression level of at least 14 biomarkers from a test sample from the subject by contacting the test sample with a plurality of agents specific to detect the expression of the at least 14 biomarkers, wherein the 14 biomarkers comprise ADRM1, CDK4, COMT, DHCR7, HMOX2, MCM2, PDXK, POP7, S100P, SNRPA, SORD, STOML2, UMPS, and a housekeeping gene; (b) normalizing the expression level of each of ADRM1, CDK4, COMT, DHCR7, HMOX2, MCM2, PDXK, POP7, S100P, SNRPA, SORD, STOML2, and UMPS to the expression level of the housekeeping gene, thereby obtaining a normalized expression level of each of ADRM41, CDK4, COMT, DHCR7, HMOX2, MCM2, PDXK, POP7, S100P, SNRPA, SORD, STOML2, and UMPS; (c) inputting each normalized expression level into an algorithm to generate a score; (d) comparing the score with a first predetermined cutoff value; and (e) producing a report, wherein the report identifies the presence of a colon cancer in the subject when the score is equal to or greater than the first predetermined cutoff value or identifies the absence of a colon cancer in the subject when the score is less than the first predetermined cutoff value, wherein the first predetermined cutoff value is 50% on a scale of 0-100%.
In one aspect, the present disclosure provides a method for determining whether a colon cancer in a subject is stable or progressive, the method comprising: (a) determining the expression level of at least 14 biomarkers from a test sample from the subject by contacting the test sample with a plurality of agents specific to detect the expression of the at least 14 biomarkers, wherein the 14 biomarkers comprise ADRM1, CDK4, COMT, DHCR7, HMOX2, MCM2, PDXK, POP7, S100P, SNRPA, SORD, STOML2, UMPS, and a housekeeping gene; (b) normalizing the expression level of each of ADRM1, CDK4, COMT, DHCR7, HMOX2, MCM2, PDXK, POP7, S100P, SNRPA, SORD, STOML2, and UMPS to the expression level of the housekeeping gene, thereby obtaining a normalized expression level of each of ADM1, CDK4, COMT, DHCR7, HMOX2, MCM2, PDXK, POP7, S100P, SNRPA, SORD, STOML2, and UMPS; (c) inputting each normalized expression level into an algorithm to generate a score; (d) comparing the score with a predetermined cutoff value; and (e) identifying that the colon cancer in the subject is progressive when the score is equal to or greater than the predetermined cutoff value or identifying that the colon cancer in the subject is stable when the score is less than the predetermined cutoff value.
In one aspect, the present disclosure provides a method for determining whether a colon cancer in a subject is stable or progressive, the method comprising: (a) determining the expression level of at least 14 biomarkers from a test sample from the subject by contacting the test sample with a plurality of agents specific to detect the expression of the at least 14 biomarkers, wherein the 14 biomarkers comprise ADRM1, CDK4, COMT, DHCR7, HMOX2, MCM2, PDXK, POP7, S100P, SNRPA, SORD, STOML2, UMPS, and a housekeeping gene; (b) normalizing the expression level of each of ADRM1, CDK4, COMT, DHCR7, HMOX2, MCM2, PDXK, POP7, S100P, SNRPA, SORD, STOML2, and UMPS to the expression level of the housekeeping gene, thereby obtaining a normalized expression level of each of ADM1, CDK4, COMT, DHCR7, HMOX2, MCM2, PDXK, POP7, S100P, SNRPA, SORD, STOML2, and UMPS; (c) inputting each normalized expression level into an algorithm to generate a score; (d) comparing the score with a second predetermined cutoff value; and (e) producing a report, wherein the report identifies that the colon cancer is progressive when the score is equal to or greater than the second predetermined cutoff value or identifies that the colon cancer is stable when the score is less than the second predetermined cutoff value, wherein the second predetermined cutoff value is 60% on a scale of 0 to 100%.
In one aspect, a method for determining the completeness of surgery in a subject having a colon cancer, the method comprising: (a) determining the expression level of at least 14 biomarkers from a test sample from the subject after the surgery by contacting the test sample with a plurality of agents specific to detect the expression of the at least 14 biomarkers, wherein the 14 biomarkers comprise ADRM1, CDK4, COMT, DHCR7, HMOX2, MCM2, PDXK, POP7, S100P, SNRPA, SORD, STOML2, UMPS, and a housekeeping gene; (b) normalizing the expression level of each of ADRM1, CDK4, COMT, DHCR7, HMOX2, MCM2, PDXK, POP7, S100P, SNRPA, SORD, STOML2, and UMPS to the expression level of the housekeeping gene, thereby obtaining a normalized expression level of each of ADRM1, CDK4, COMT, DHCR7, HMOX2, MCM2, PDXK, POP7, S100P, SNRPA, SORD, STOML2, and UMPS; (c) inputting each normalized expression level into an algorithm to generate a score; (d) comparing the score with a predetermined cutoff value; and (e) identifying that the colon cancer in the subject is not completely removed when the score is equal to or greater than the predetermined cutoff value or identifying that the colon cancer in the subject is completely removed when the score is less than the predetermined cutoff value.
In one aspect, the present disclosure provides a method for determining the completeness of surgery in a subject having a colon cancer, the method comprising: (a) determining the expression level of at least 14 biomarkers from a test sample from the subject after the surgery by contacting the test sample with a plurality of agents specific to detect the expression of the at least 14 biomarkers, wherein the 14 biomarkers comprise ADRM1, CDK4, COMT, DHCR7, HMOX2, MCM2, PDXK, POP7, S100P, SNRPA, SORD, STOML2, UMPS, and a housekeeping gene; (b) normalizing the expression level of each of ADRM1, CDK4, COMT, DHCR7, HMOX2, MCM2, PDXK, POP7, S100P, SNRPA, SORD, STOML2, and UMPS to the expression level of the housekeeping gene, thereby obtaining a normalized expression level of each of ADRM1, CDK4, COMT, DHCR7, HMOX2, MCM2, PDXK, POP7, S100P, SNRPA, SORD, STOML2, and UMPS; (c) inputting each normalized expression level into an algorithm to generate a score; (d) comparing the score with a first predetermined cutoff value; and (e) producing a report, wherein the report identifies that the colon cancer is not completely removed when the score is equal to or greater than the first predetermined cutoff value or identifies that the colon cancer is completely removed when the score is less than the first predetermined cutoff value, wherein the first predetermined cutoff value is 50% on a scale of 0-100%.
In one aspect, the present disclosure provides a method comprising: (a) determining the expression level of at least 14 biomarkers from a test sample from a subject by contacting the test sample with a plurality of agents specific to detect the expression of the at least 14 biomarkers, wherein the 14 biomarkers comprise ADRM1, CDK4, COMT, DHCR7, HMOX2, MCM2, PDXK, POP7, S100P, SNRPA, SORD, STOML2, UMPS, and a housekeeping gene; (b) normalizing the expression level of each of ADRM1, CDK4, COMT, DHCR7, HMOX2, MCM2, PDXK, POP7, S100P, SNRPA, SORD, STOML2, and UMPS to the expression level of the housekeeping gene, thereby obtaining a normalized expression level of each of ADM1, CDK4, COMT, DHCR7, HMOX2, MCM2, PDXK, POP7, S100P, SNRPA, SORD, STOML2, and UMPS; (c) inputting each normalized expression level into an algorithm to generate a score; (d) comparing the score with a predetermined cutoff value; and (e) administering a first therapy to the subject when the score is equal to or greater than the predetermined cutoff value.
In one aspect, the present disclosure provides a method for evaluating the response of a subject having a colon cancer to a first therapy, the method comprising: (1) at a first time point: (a) determining the expression level of at least 14 biomarkers from a first test sample from the subject by contacting the first test sample with a plurality of agents specific to detect the expression of the at least 14 biomarkers, wherein the 14 biomarkers comprise ADM1, CDK4, COMT, DHCR7, HMOX2, MCM2, PDXK, POP7, S100P, SNRPA, SORD, STOML2, UMPS, and a housekeeping gene; (b) normalizing the expression level of each of ADM1, CDK4, COMT, DHCR7, HMOX2, MCM2, PDXK, POP7, S100P, SNRPA, SORD, STOML2, and UMPS to the expression level of the housekeeping gene, thereby obtaining a normalized expression level of each of ADRM1, CDK4, COMT, DHCR7, HMOX2, MCM2, PDXK, POP7, S100P, SNRPA, SORD, STOML2, and UMPS; (c) inputting each normalized expression level into an algorithm to generate a first score; (2) at a second time point, wherein the second time point is after the first time point and after the administration of the therapy to the subject: (a) determining the expression level of at least 14 biomarkers from a second test sample from the subject by contacting the second test sample with a plurality of agents specific to detect the expression of the at least 14 biomarkers, wherein the 14 biomarkers comprise ADRM1, CDK4, COMT, DHCR7, HMOX2, MCM2, PDXK, POP7, S100P, SNRPA, SORD, STOML2, UMPS, and the housekeeping gene; (b) normalizing the expression level of each of ADRM1, CDK4, COMT, DHCR7, HMOX2, MCM2, PDXK, POP7, S100P, SNRPA, SORD, STOML2, and UMPS to the expression level of the housekeeping gene, thereby obtaining a normalized expression level of each of ADM1, CDK4, COMT, DHCR7, HMOX2, MCM2, PDXK, POP7, S100P, SNRPA, SORD, STOML2, and UMPS; (c) inputting each normalized expression level into the algorithm to generate a second score; (3) comparing the first score with the second score; and (4) identifying that the subject is responsive to the first therapy when the second score is significantly decreased as compared to the first score or identifying that the subject is not responsive to the first therapy when the second score is not significantly decreased as compared to the first score.
In one aspect, the present disclosure provides a method for evaluating the response of a subject having a colon cancer to a therapy, the method comprising: (1) at a first time point, performing the following steps that include (a) determining the expression level of at least 14 biomarkers from a first test sample from the subject by contacting the first test sample with a plurality of agents specific to detect the expression of the at least 14 biomarkers, wherein the 14 biomarkers comprise ADRM1, CDK4, COMT, DHCR7, HMOX2, MCM2, PDXK, POP7, S100P, SNRPA, SORD, STOML2, UMPS, and a housekeeping gene; (b) normalizing the expression level of each of ADRM1, CDK4, COMT, DHCR7, HMOX2, MCM2, PDXK, POP7, S100P, SNRPA, SORD, STOML2, and UMPS to the expression level of the housekeeping gene, thereby obtaining a normalized expression level of each of ADM1, CDK4, COMT, DHCR7, HMOX2, MCM2, PDXK, POP7, S100P, SNRPA, SORD, STOML2, and UMPS; (c) inputting each normalized expression level into an algorithm to generate a first score; and (2) at a second time point, performing the following steps that include (d) determining the expression level of at least 14 biomarkers from a second test sample from the subject by contacting the second test sample with a plurality of agents specific to detect the expression of the at least 14 biomarkers, wherein the 14 biomarkers comprise ADRM1, CDK4, COMT, DHCR7, HMOX2, MCM2, PDXK, POP7, S100P, SNRPA, SORD, STOML2, UMPS, and the housekeeping gene; (e) normalizing the expression level of each of ADRM1, CDK4, COMT, DHCR7, HMOX2, MCM2, PDXK, POP7, S100P, SNRPA, SORD, STOML2, and UMPS to the expression level of the housekeeping gene, thereby obtaining a normalized expression level of each of ADM1, CDK4, COMT, DHCR7, HMOX2, MCM2, PDXK, POP7, S100P, SNRPA, SORD, STOML2, and UMPS; (f) inputting each normalized expression level into the algorithm to generate a second score, wherein the second time point is after the first time point and after the administration of the therapy to the subject; (3) comparing the first score with the second score; and (4) producing a report, wherein the report identifies that the subject is responsive to the therapy when the second score is significantly decreased as compared to the first score or identifies that the subject is not responsive to the therapy when the second score is not significantly decreased as compared to the first score.
In some aspects, a method of the present disclosure can further comprise continuing to administer a first therapy to a subject when a second score is significantly decreased as compared to a first score.
In some aspects, a method of the present disclosure can further comprise discontinuing administration of a first therapy to a subject when a second score is not significantly decreased as compared to a first score.
In some aspects, a method of the present disclosure can further comprise administering a second therapy to a subject when a second score is not significantly decreased as compared to a first score.
In some aspects, a second score is significantly decreased as compared to a first score when the second score is at least 25% less than the first score.
In some aspects, a predetermined cutoff value can be 50% on a scale of 0-100%. A predetermined cutoff value can be 60% on a scale of 0-100%.
In some aspects of any one of the methods disclosed herein, a housekeeping gene can be selected from the group consisting of MRPL19, PSMC4, SF3A1, PUM1, ACTB, GAPD, GUSB, RPLP0, TFRC, MORF4L1, 18S, PPIA, PGK1, RPL13A, B2M, YWHAZ, SDHA, and HPRT1. For example, the housekeeping gene can be MORF4L1.
In some aspects, a method of the present disclosure can have a sensitivity greater than 85%. In some aspects, a method of the present disclosure can have a specificity of greater than 85%.
In some aspects, a biomarker can comprise RNA, cDNA, protein or any combination thereof.
In some aspects, wherein when the biomarker is RNA, the RNA can be reverse transcribed to produce cDNA, and the produced cDNA expression level can be detected.
In some aspects, a biomarker or the expression of a biomarker can be detected by forming a complex between the biomarker and a labeled probe or primer.
In some aspects, when a biomarker is protein, the protein can be detected by forming a complex between the protein and a labeled antibody.
In some aspects, when a biomarker is RNA or cDNA, the RNA or cDNA can be detected by forming a complex between the RNA or cDNA and a labeled nucleic acid probe or primer. A complex between the RNA or cDNA and the labeled nucleic acid probe or primer can be a hybridization complex.
In some aspects, a predetermined cutoff value can be derived from a plurality of reference samples obtained from subjects not having or not diagnosed with a neoplastic disease. The neoplastic disease can be colon cancer.
In some aspects, an algorithm can be XGBoost (XGB), Random Forest (RF), glmnet, cforest, Classification and Regression Trees for Machine Learning (CART), treebag, K-Nearest Neighbors (kNN), neural network (nnet), Support Vector Machine radial (SVM-radial), Support Vector Machine linear (SVM-linear), Naïve Bayes (NB), multilayer perceptron (mlp) or any combination thereof.
In some aspects, the methods of the present disclosure can further comprise administering to a subject a first therapy when a score is equal to or greater than a predetermined cutoff.
In some aspects, a first time point can be prior to the administration of a first therapy to the subject. A first time point can be after the administration of the first therapy to the subject.
In some aspects, a therapy can comprise anti-cancer therapy, surgery, chemotherapy, targeted drug therapy, radiation therapy, immunotherapy or any combination thereof.
In some aspects, surgery can comprise removing a polyp during a colonoscopy, endoscopic mucosal resection, a partial colectomy, an ostomy, removing at least one cancerous lesion from the liver, or any combination thereof.
In some aspects, chemotherapy can comprise FOLFOX, FOLFIRI, a combination of 5-FU and leucovorin, capecitabine, irinotecan, CapeOx or any combination thereof.
In some aspects, targeted drug therapy can comprise bevacizumab, cetuximab, panitumumab, regorafenib, a combination of trifluridine and tipiracil, a EGFR TKI inhibitor or any combination thereof.
In some aspects, anti-cancer therapy can comprise anti-colon cancer therapy.
In some aspects, immunotherapy can comprise pembrolizumab, nivolumab or a combination of pembrolizumab and nivolumab.
In some aspects, a test sample can be blood, serum, plasma, neoplastic tissue or any combination thereof. A reference sample can be blood, serum, plasma, non-neoplastic tissue or any combination thereof.
Any of the above aspects can be combined with any other aspect.
Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this disclosure belongs. In the Specification, the singular forms also include the plural unless the context clearly dictates otherwise; as examples, the terms “a,” “an,” and “the” are understood to be singular or plural and the term “or” is understood to be inclusive. By way of example, “an element” means one or more element. Throughout the specification the word “comprising,” or variations such as “comprises” or “comprising,” will be understood to imply the inclusion of a stated element, integer or step, or group of elements, integers or steps, but not the exclusion of any other element, integer or step, or group of elements, integers or steps. About can be understood as within 10%, 9%, 8%, 7%, 6%, 5%, 4%, 3%, 2%, 1%, 0.5%, 0.1%, 0.05%, or 0.01% of the stated value. Unless otherwise clear from the context, all numerical values provided herein are modified by the term “about.”
Although methods and materials similar or equivalent to those described herein can be used in the practice or testing of the present disclosure, suitable methods and materials are described below. All publications, patent applications, patents, and other references mentioned herein are incorporated by reference in their entirety. The references cited herein are not admitted to be prior art to the claimed invention. In the case of conflict, the present Specification, including definitions, will control. In addition, the materials, methods, and examples are illustrative only and are not intended to be limiting. Other features and advantages of the disclosure will be apparent from the following detailed description and claim.
BRIEF DESCRIPTION OF THE DRAWINGS
FIGS. 1A-1B are graphs showing normalized gene expression of the 13 gene signature in colon mucosa (FIG. 1A) and cell lines (FIG. 1B). Gene expression was significantly (p<0.0001) elevated in colon cancer samples (n=7) compared to matched normal mucosa (n=7). Levels were ˜20-fold elevated in colon cancer tumor tissue than in normal mucosa. All genes were expressed in three different colon cancer cell lines. Levels were ˜1000× elevated compared to normal mucosa. Horizontal lines identify median normalized expression of the 13 genes.
FIGS. 2A-2B are graphs showing receiver operator curve analysis of the test set (FIG. 2A) and independent set (FIG. 2B). Each cohort included 136 cancers and 60 controls. The AUROC in the test set was 0.9 and the Youden J index was 0.71. In the independent set the AUROC was 0.86 with a Youden index of 0.6. Z-statistics ranged 11.2-15.6 and were highly significant (p<0.0001). The sensitivity and specificity of the test ranged 85-87.5% and 75-83%, respectively.
FIGS. 3A-3B are graphs showing that gene expression in the entire cohort (controls: n=120; colon cancer cases: n=272) identified levels were significantly (p<0.0001) elevated in cases (62.7±14%) versus controls (34.6±18%) (FIG. 3A). The AUROC was 0.88, p<0.0001 (FIG. 3B). Horizontal lines identify median expression of the normalized 13 gene signature (ColoTest).
FIGS. 4A-4B are graphs showing decision curve analysis (FIG. 4A) and risk analysis (FIG. 4B) for the ColoTest. This exhibited >50% standardized predictive benefit up to a risk threshold of 80%. The probit risk assessment plot identified a ColoTest score >50% was 75% accurate for predicting colon cancer in a blood sample. This was increased to >80% at a ColoTest score >60%.
FIG. 5 is a graph showing the effect of surgery on the ColoTest. Levels prior to surgery are elevated (84±6%). In those with no evidence of disease (NED) levels were reduced by surgery to 14±9% (*p=0.0001). In those with disease (D) remaining after surgery, levels remained similar to pre-surgical values (74±4%).
FIGS. 6A-6C are graphs showing ColoTest scores in stable and progressive disease. Test scores were not significantly different between those identified as stable and those with progressive disease at the time of assessment (FIG. 6A). Of the 17 with stable disease, 12 exhibited disease progression in the 3 month follow-up. Levels in those who truly had demonstrable stable disease were low (16±10%) (FIG. 6B). In those who did progress in the 3 months levels were not different to those that had progressive disease (73±16% vs. 68±25%). The AUROC for differentiating stable from progressing/progressive disease was 0.97, p<0.0001 (FIG. 6C).
FIG. 7 is a graph showing comparison of AUROC between the ColoTest and CEA for differentiating stable from progressive disease. The ColoTest was significantly more sensitive than CEA (difference in AUC: 0.18, z-statistic: 2.1, p=0.03).
FIG. 8 is a graph showing the effect of treatment on the ColoTest. Levels prior to treatment are elevated (82±9%). In those who responded to therapy with disease stabilization, levels were reduced to 14±7% (*p<0.0001). In those that exhibited disease progression because of treatment failure, levels were elevated (69±21%).
 DETAILED DESCRIPTION OF THE INVENTION
The details of the invention are set forth in the accompanying description below. Although methods and materials similar or equivalent to those described herein can be used in the practice or testing of the present invention, illustrative methods and materials are now described. Other features, objects, and advantages of the invention will be apparent from the description and from the claims. In the specification and the appended claims, the singular forms also include the plural unless the context clearly dictates otherwise. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. All patents and publications cited in this specification are incorporated herein by reference in their entireties.
Colon cancer is cancer of the large intestine (colon). Symptoms of colon cancer include, but are not limited to: (a) a change in bowel habits, (b) rectal bleeding or blood in the stool, (c) persistent abdominal discomfort, such as cramps, gas or pain, (d) a feeling that the bowel doesn't empty completely, (e) weakness or fatigue, and (f) unexplained weight loss.
Described herein are methods to quantitate (score) the circulating colon cancer molecular signature with high sensitivity and specificity for purposes including, but not limited to, detecting a colon cancer, determining whether a colon cancer is stable or progressive, determining the completeness of surgery, and evaluating the response to a colon cancer therapy. Specifically, the present invention is based on the discovery that the expression levels of ADRM1, CDK4, COMT, DHCR7, HMOX2, MCM2, PDXK, POP7, S100P, SNRPA, SORD, STOML2, and UMPS, normalized by the expression level of a housekeeping gene such as MORF4L1, are elevated in subjects having colon cancers as compared to healthy subjects.
Accordingly, the present disclosure provides a method for detecting a colon cancer in a subject in need thereof, the method comprising: (a) determining the expression level of at least 14 biomarkers from a test sample from the subject by contacting the test sample with a plurality of agents specific to detect the expression of the at least 14 biomarkers, wherein the 14 biomarkers comprise ADRM1, CDK4, COMT, DHCR7, HMOX2, MCM2, PDXK, POP7, S100P, SNRPA, SORD, STOML2, UMPS, and a housekeeping gene; (b) normalizing the expression level of each of ADRM1, CDK4, COMT, DHCR7, HMOX2, MCM2, PDXK, POP7, S100P, SNRPA, SORD, STOML2, and UMPS to the expression level of the housekeeping gene, thereby obtaining a normalized expression level of each of ADRM1, CDK4, COMT, DHCR7, HMOX2, MCM2, PDXK, POP7, S100P, SNRPA, SORD, STOML2, and UMPS; (c) inputting each normalized expression level into an algorithm to generate a score; (d) comparing the score with a first predetermined cutoff value; and (e) identifying the presence of a colon cancer in the subject when the score is equal to or greater than the predetermined cutoff value or identifying the absence of a colon cancer in the subject when the score is less than the predetermined cutoff value.
In some aspects of the preceding method, step (e) can comprise producing a report, wherein the report identifies the presence of a colon cancer in the subject when the score is equal to or greater than the first predetermined cutoff value or identifies the absence of a colon cancer in the subject when the score is less than the first predetermined cutoff value.
In some aspects, the preceding method can further comprise administering to the subject a first therapy. The preceding method can further comprise administering to the subject a first therapy when the score is equal to or greater than the predetermined cutoff.
The present disclosure also provides a method for determining whether a colon cancer in a subject is stable or progressive, the method comprising: (a) determining the expression level of at least 14 biomarkers from a test sample from the subject by contacting the test sample with a plurality of agents specific to detect the expression of the at least 14 biomarkers, wherein the 14 biomarkers comprise ADRM1, CDK4, COMT, DHCR7, HMOX2, MCM2, PDXK, POP7, S100P, SNRPA, SORD, STOML2, UMPS, and a housekeeping gene; (b) normalizing the expression level of each of ADRM1, CDK4, COMT, DHCR7, HMOX2, MCM2, PDXK, POP7, S100P, SNRPA, SORD, STOML2, and UMPS to the expression level of the housekeeping gene, thereby obtaining a normalized expression level of each of ADRM1, CDK4, COMT, DHCR7, HMOX2, MCM2, PDXK, POP7, S100P, SNRPA, SORD, STOML2, and UMPS; (c) inputting each normalized expression level into an algorithm to generate a score; (d) comparing the score with a second predetermined cutoff value; and (e) identifying that the colon cancer in the subject is progressive when the score is equal to or greater than the predetermined cutoff value or identifying that the colon cancer in the subject is stable when the score is less than the predetermined cutoff value.
In some aspects of the preceding method, step (e) can comprise producing a report, wherein the report identifies that the colon cancer is progressive when the score is equal to or greater than the second predetermined cutoff value or identifies that the colon cancer is stable when the score is less than the second predetermined cutoff value.
In some aspects, the preceding method can further comprise administering to the subject a first therapy. The preceding method can further comprise administering to the subject a first therapy when the score is equal to or greater than the predetermined cutoff.
In some aspects, the method further comprises treating the subject with a progressive colon cancer with surgery, chemotherapy, targeted drug therapy, radiation therapy, immunotherapy, or a combination thereof.
The present disclosure also provides a method for determining the completeness of surgery in a subject having a colon cancer, the method comprising: (a) determining the expression level of at least 14 biomarkers from a test sample from the subject after the surgery by contacting the test sample with a plurality of agents specific to detect the expression of the at least 14 biomarkers, wherein the 14 biomarkers comprise ADM1, CDK4, COMT, DHCR7, HMOX2, MCM2, PDXK, POP7, S100P, SNRPA, SORD, STOML2, UMPS, and a housekeeping gene; (b) normalizing the expression level of each of ADRM1, CDK4, COMT, DHCR7, HMOX2, MCM2, PDXK, POP7, S100P, SNRPA, SORD, STOML2, and UMPS to the expression level of the housekeeping gene, thereby obtaining a normalized expression level of each of ADRM1, CDK4, COMT, DHCR7, HMOX2, MCM2, PDXK, POP7, S100P, SNRPA, SORD, STOML2, and UMPS; (c) inputting each normalized expression level into an algorithm to generate a score; (d) comparing the score with a first predetermined cutoff value; and (e) identifying that the colon cancer in the subject is not completely removed when the score is equal to or greater than the predetermined cutoff value or identifying that the colon cancer in the subject is completely removed when the score is less than the predetermined cutoff value.
In some aspects of the preceding method, step (e) can comprise producing a report, wherein the report identifies that the colon cancer is not completely removed when the score is equal to or greater than the first predetermined cutoff value or identifies that the colon cancer is completely removed when the score is less than the first predetermined cutoff value.
In some aspects, the preceding method can further comprise administering to the subject a first therapy. The preceding method can further comprise administering to the subject a first therapy when the score is equal to or greater than the predetermined cutoff.
The present disclosure also provides a method comprising: (a) determining the expression level of at least 14 biomarkers from a test sample from a subject by contacting the test sample with a plurality of agents specific to detect the expression of the at least 14 biomarkers, wherein the 14 biomarkers comprise ADM1, CDK4, COMT, DHCR7, HMOX2, MCM2, PDXK, POP7, S100P, SNRPA, SORD, STOML2, UMPS, and a housekeeping gene; (b) normalizing the expression level of each of ADRM1, CDK4, COMT, DHCR7, HMOX2, MCM2, PDXK, POP7, S100P, SNRPA, SORD, STOML2, and UMPS to the expression level of the housekeeping gene, thereby obtaining a normalized expression level of each of ADRM1, CDK4, COMT, DHCR7, HMOX2, MCM2, PDXK, POP7, S100P, SNRPA, SORD, STOML2, and UMPS; (c) inputting each normalized expression level into an algorithm to generate a score; (d) comparing the score with a predetermined cutoff value; and (e) administering a first therapy to the subject when the score is equal to or greater than the predetermined cutoff value.
The response of a subject having a colon cancer to a therapy can also be evaluated by comparing the scores determined by the same algorithm at different time points of the therapy. For example, the first time point can be prior to or after the administration of the therapy to the subject; the second time point is after the first time point and after the administration of the therapy to the subject. A first score is generated at the first time point, and a second score is generated at the second time point. When the second score is significantly decreased as compared to the first score, the subject is considered to be responsive to the therapy.
Accordingly, the present disclosure provides a method for evaluating the response of a subject having a colon cancer to a first therapy, the method comprising: (1) at a first time point: (a) determining the expression level of at least 14 biomarkers from a first test sample from the subject by contacting the first test sample with a plurality of agents specific to detect the expression of the at least 14 biomarkers, wherein the 14 biomarkers comprise ADRM1, CDK4, COMT, DHCR7, HMOX2, MCM2, PDXK, POP7, S100P, SNRPA, SORD, STOML2, UMPS, and a housekeeping gene; (b) normalizing the expression level of each of ADRM1, CDK4, COMT, DHCR7, HMOX2, MCM2, PDXK, POP7, S100P, SNRPA, SORD, STOML2, and UMPS to the expression level of the housekeeping gene, thereby obtaining a normalized expression level of each of ADRM1, CDK4, COMT, DHCR7, HMOX2, MCM2, PDXK, POP7, S100P, SNRPA, SORD, STOML2, and UMPS; (c) inputting each normalized expression level into an algorithm to generate a first score; (2) at a second time point, wherein the second time point is after the first time point and after the administration of the therapy to the subject: (a) determining the expression level of at least 14 biomarkers from a second test sample from the subject by contacting the second test sample with a plurality of agents specific to detect the expression of the at least 14 biomarkers, wherein the 14 biomarkers comprise ADM1, CDK4, COMT, DHCR7, HMOX2, MCM2, PDXK, POP7, S100P, SNRPA, SORD, STOML2, UMPS, and the housekeeping gene; (b) normalizing the expression level of each of ADRM1, CDK4, COMT, DHCR7, HMOX2, MCM2, PDXK, POP7, S100P, SNRPA, SORD, STOML2, and UMPS to the expression level of the housekeeping gene, thereby obtaining a normalized expression level of each of ADRM1, CDK4, COMT, DHCR7, HMOX2, MCM2, PDXK, POP7, S100P, SNRPA, SORD, STOML2, and UMPS; (c) inputting each normalized expression level into the algorithm to generate a second score; (3) comparing the first score with the second score; and (4) identifying that the subject is responsive to the first therapy when the second score is significantly decreased as compared to the first score or identifying that the subject is not responsive to the first therapy when the second score is not significantly decreased as compared to the first score.
In some aspects of the preceding method, step (4) can comprise producing a report, wherein the report identifies that the subject is responsive to the first therapy when the second score is significantly decreased as compared to the first score or identifies that the subject is not responsive to the first therapy when the second score is not significantly decreased as compared to the first score.
In some aspects of the preceding method, the second score is significantly decreased as compared to the first score when the second score is at least about 10% less than the first score, or at least about 20% less than the first score, or at least about 25% less than the first score, at least about 40% less than the first score, at least about 50% less than the first score, or at least about 60% less than the first score, or at least about 70% less than the first score, or at least about 75% less than the first score, or at least about 80% less than the first score, or at least about 90% less than the first score, or at least about 95% less than the first score or at least about 95% less than the first score. In some aspects, when the second score is not significantly decreased as compared to the first score, the subject is considered to be not responsive to the therapy.
In some aspects of the preceding method, a first time point can be prior to the administration of a first therapy to the subject. A first time point can be after the administration of a first therapy to the subject.
In some aspects, the preceding method can further comprise continuing to administer the first therapy to the subject when the second score is significantly decreased as compared to the first score.
In some aspects, the preceding method can further comprise discontinuing administration of the first therapy to the subject when the second score is not significantly decreased as compared to the first score.
In some aspects, the preceding method can further comprise administering a second therapy to the subject when the second score is not significantly decreased as compared to the first score.
In some aspects of the methods of the present disclosure, a predetermined cutoff value can be about 50% on a scale of 0-100%. A predetermined cutoff value can be about 60% on a scale of 0-100%. A predetermine cutoff value can be about 10%, or about 20%, or about 30%, or about 40%, or about 70%, or about 80%, or about 90% on a scale of 0-100%.
In some aspects of the methods of the present disclosure, a test sample can be any biological fluid obtained from the subject. A test sample can be blood, serum, plasma, neoplastic tissue or any combination thereof. In some aspects, the test sample is blood. In some aspects, the test sample is serum. In some aspects, the test sample is plasma.
In some aspects of the methods of the present disclosure, a housekeeping gene can comprise, but is not limited to, MRPL19, PSMC4, SF3A1, PUM1, ACTB, GAPD, GUSB, RPLP0, TFRC, MORF4L1, 18S, PPIA, PGK1, RPL13A, B2M, YWHAZ, SDHA, and HPRT1. In some aspects, the housekeeping gene is MORF4L1.
The methods of the present disclosure can have a sensitivity of at least about 50%, or at least about 60%, or at least about 70%, or at least about 75%, or at least about 80%, or at least about 85%, or at least about 90%, or at least about 95%, or at least about 99%. The methods of the present disclosure can have a sensitivity of greater than about 50%, or greater than about 60%, or greater than about 70%, or greater than about 75%, or greater than about 80%, or greater than about 85%, or greater than about 90%, or greater than about 95%, or greater than about 99%.
The methods of the present disclosure can have a specificity of at least about 50%, or at least about 60%, or at least about 70%, or at least about 75%, or at least about 80%, or at least about 85%, or at least about 90%, or at least about 95%, or at least about 99%. The methods of the present disclosure can have a specificity of greater than about 50%, or greater than about 60%, or greater than about 70%, or greater than about 75%, or greater than about 80%, or greater than about 85%, or greater than about 90%, or greater than about 95%, or greater than about 99%.
The methods of the present disclosure can have an accuracy of at least about 50%, or at least about 60%, or at least about 70%, or at least about 75%, or at least about 80%, or at least about 85%, or at least about 90%, or at least about 95%, or at least about 99%. The methods of the present disclosure can have an accuracy of greater than about 50%, or greater than about 60%, or greater than about 70%, or greater than about 75%, or greater than about 80%, or greater than about 85%, or greater than about 90%, or greater than about 95%, or greater than about 99%.
In some aspects of the methods of the present disclosure, a predetermined cutoff value can be derived from a plurality of reference samples obtained from subjects not having or not diagnosed with a neoplastic disease. In some aspects, the neoplastic disease can be colon cancer.
The plurality of reference samples can comprise about 2-500, 2-200, 10-100, or 20-80 reference samples. Each reference sample produces a score using the algorithm, and the first predetermined cutoff value can be an arithmetic mean of these scores. Each reference sample can be blood, serum, plasma, or non-neoplastic tissue. In some aspects, each reference sample is blood. In some aspects, each reference sample is of the same type as the test sample.
Each of the biomarkers disclosed herein may have one or more transcript variants. The methods disclosed herein can measure the expression level of any one of the transcript variants for each biomarker.
The expression level can be measured in a number of ways, including, but not limited to: measuring the mRNA encoded by the selected genes; measuring the amount of protein encoded by the selected genes; and measuring the activity of the protein encoded by the selected genes.
In some aspects of the methods of the present disclosure, a biomarker can be RNA, cDNA, protein or any combination thereof. When the biomarker is RNA, the RNA can be reverse transcribed to produce cDNA (such as by RT-PCR), and the produced cDNA expression level can be detected. The expression level of a biomarker can be detected by forming a complex between the biomarker and a labeled probe or primer. When the biomarker is RNA or cDNA, the RNA or cDNA can be detected by forming a complex between the RNA or cDNA and a labeled nucleic acid probe or primer. The complex between the RNA or cDNA and the labeled nucleic acid probe or primer can be a hybridization complex.
In some aspects of the methods of the present disclosure, gene expression can be detected by microarray analysis. Differential gene expression can also be identified, or confirmed using the microarray technique. Thus, the expression profile biomarkers can be measured in either fresh or fixed tissue, using microarray technology. In this method, polynucleotide sequences of interest (including cDNAs and oligonucleotides) are plated, or arrayed, on a microchip substrate. The arrayed sequences are then hybridized with specific DNA probes from cells or tissues of interest. The source of mRNA typically is total RNA isolated from a biological sample, and corresponding normal tissues or cell lines may be used to determine differential expression.
In some aspects of microarray techniques, PCR amplified inserts of cDNA clones are applied to a substrate in a dense array. In some aspects, at least 10,000 nucleotide sequences are applied to the substrate. The microarrayed genes, immobilized on the microchip at 10,000 elements each, are suitable for hybridization under stringent conditions. Fluorescently labeled cDNA probes may be generated through incorporation of fluorescent nucleotides by reverse transcription of RNA extracted from tissues of interest. Labeled cDNA probes applied to the chip hybridize with specificity to each spot of DNA on the array. After stringent washing to remove non-specifically bound probes, the microarray chip is scanned by a device such as, confocal laser microscopy or by another detection method, such as a CCD camera. Quantitation of hybridization of each arrayed element allows for assessment of corresponding mRNA abundance. With dual color fluorescence, separately labeled cDNA probes generated from two sources of RNA are hybridized pair-wise to the array. The relative abundance of the transcripts from the two sources corresponding to each specified gene is thus determined simultaneously. Microarray analysis can be performed by commercially available equipment, following manufacturer's protocols.
In some aspects of the methods of the present disclosure, the biomarkers can be detected in a biological sample using qRT-PCR. The first step in gene expression profiling by RT-PCR is extracting RNA from a biological sample followed by the reverse transcription of the RNA template into cDNA and amplification by a PCR reaction. The reverse transcription reaction step is generally primed using specific primers, random hexamers, or oligo-dT primers, depending on the goal of expression profiling. The two commonly used reverse transcriptases are avilo myeloblastosis virus reverse transcriptase (AMV-RT) and Moloney murine leukemia virus reverse transcriptase (MLV-RT).
In some aspects of the methods of the present disclosure, when the biomarker is a protein, the protein can be detected by forming a complex between the protein and a labeled antibody. The label can be any label for example a fluorescent label, chemiluminescence label, radioactive label, etc. Exemplary methods for protein detection include, but are not limited to, enzyme immunoassay (EIA), radioimmunoassay (MA), Western blot analysis and enzyme linked immunoabsorbant assay (ELISA). For example, the biomarker can be detected in an ELISA, in which the biomarker antibody is bound to a solid phase and an enzyme-antibody conjugate is employed to detect and/or quantify biomarker present in a sample. Alternatively, a western blot assay can be used in which solubilized and separated biomarker is bound to nitrocellulose paper. The combination of a highly specific, stable liquid conjugate with a sensitive chromogenic substrate allows rapid and accurate identification of samples.
In some aspects of the methods of the present disclosure, the methods described herein can have a specificity, sensitivity, and/or accuracy of at least 75%, 80%, 85%, 90%, 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, or 99%.
In some aspects of the methods of the present disclosure, a labeled probe, a labeled primer, a labeled antibody or a labeled nucleic acid can comprise a fluorescent label.
Any algorithm that can generate a score for a sample by assessing where that sample value falls onto a prediction model generated using different techniques, e.g., decision trees, can be used in the methods disclosed herein. The algorithm analyzes the data (i.e., expression levels) and then assigns a score. In some aspects, the algorithm can be a machine-learning algorithm. Exemplary algorithms that can be used in the methods disclosed herein can include, but are not limited to, XGBoost (XGB), Random Forest (RF), glmnet, cforest, Classification and Regression Trees for Machine Learning (CART), treebag, K-Nearest Neighbors (kNN), neural network (nnet), Support Vector Machine radial (SVM-radial), Support Vector Machine linear (SVM-linear), Naïve Bayes (NB), multilayer perceptron (mlp) or any combination thereof.
In some aspects of the methods of the present disclosure, the algorithm can be XGB (also called XGBoost). XGB is an implementation of gradient boosted decision trees designed for speed and performance.
In some aspects of the methods of the present disclosure, a therapy can comprise anti-cancer therapy, surgery, chemotherapy, targeted drug therapy, radiation therapy, immunotherapy, or any combination thereof.
In some aspects of the methods of the present disclosure, surgery can comprise removing a polyp during a colonoscopy, endoscopic mucosal resection, a partial colectomy, an ostomy, removing at least one cancerous lesion from the liver, or any combination thereof.
In some aspects of the methods of the present disclosure, anti-cancer therapy can comprise anti-colon cancer therapy.
In some aspects of the methods of the present disclosure, chemotherapy can comprise FOLFOX, FOLFIRI, a combination of 5-FU and leucovorin, capecitabine, irinotecan, CapeOx or any combination thereof.
In some aspects of the methods of the present disclosure, targeted drug therapy can comprise bevacizumab, cetuximab, panitumumab, regorafenib, a combination of trifluridine and tipiracil, an EGFR TKI inhibitor or any combination thereof.
In some aspects of the methods of the present disclosure, immunotherapy can comprise pembrolizumab, nivolumab or a combination of pembrolizumab and nivolumab.
For early-stage colon cancer, a minimally invasive approach to surgery can be used to remove the cancer. For example, if the cancer is completely contained within a polyp, the polyp can be removed during a colonoscopy. Endoscopic mucosal resection can be performed to remove larger polyps. Polyps that cannot be removed during a colonoscopy may be removed using laparoscopic surgery.
If the cancer has grown into or through the colon, partial colectomy can be performed to remove the part of the colon that contains the cancer, along with a margin of normal tissue on either side of the cancer. When it's not possible to reconnect the healthy portions of the colon or rectum, an ostomy can be performed to create an opening in the wall of the abdomen from a portion of the remaining bowel for the elimination of stool into a bag that fits securely over the opening. Lymph node removal can also be performed.
For advanced colon cancer, an operation to relieve a blockage of the colon or other conditions can also be performed. In specific cases where the cancer has spread only to the liver, surgery to remove the cancerous lesion from the liver can be performed.
For chemotherapies, either the FOLFOX (5-FU, leucovorin, and oxaliplatin) or CapeOx (capecitabine and oxaliplatin) regimens are used most often, but some patients may get 5-FU with leucovorin or capecitabine alone based on their age and health needs. Irinotecan can also be used as a chemotherapeutic agent for treating a colon cancer.
Targeted drug therapies target specific malfunctions that allow cancer cells to grow. These therapies include, but are not limited to, bevacizumab, cetuximab, panitumumab, ramucirumab, regorafenib, ziv-aflibercept, a combination of trifluridine and tipiracil, and an EGFR TKI inhibitor.
Immunotherapies for colon cancer include, but are not limited to, pembrolizumab (Keytruda®) and nivolumab (Opdivo®).
The sequence information of the colon cancer biomarkers and housekeepers is shown in Table 1.
TABLE 1
Colon Cancer Biomarker/Housekeeper Sequence Information
SEQ
Gene RefSeq ID
Name Accession Sequence NO:
ADRM1 NM_007002.3 gttagagccggctgcgcggcttacggggctcaatcggcgg 1
cgagagcggcaggcggggcgggccgaacgcgggtttccgg
cggggcccggcaggcgccgaggaggaagagcgagcccgga
cggcgcctctcgaacgagtgtgggcgcgaggcaggatgac
gacctcaggcgcgctctttccaagcctggtgccaggctct
cggggcgcctccaacaagtacttggtggagtttcgggcgg
gaaagatgtccctgaaggggaccaccgtgactccggataa
gcggaaagggctggtgtacattcagcagacggacgactcg
cttattcacttctgctggaaggacaggacgtccgggaacg
tggaagacgacttgatcatcttccctgacgactgtgagtt
caagcgggtgccgcagtgccccagcgggagggtctacgtg
ctgaagttcaaggcagggtccaagcggcttttcttctgga
tgcaggaacccaagacagaccaggatgaggagcattgccg
gaaagtcaacgagtatctgaacaaccccccgatgcctggg
gcgctgggggccagcggaagcagcggccacgaactctctg
cgctaggcggtgagggtggcctgcagagcctgctgggaaa
catgagccacagccagctcatgcagctcatcggaccagcc
ggcctcggaggactgggtgggctgggggccctgactggac
ctggcctggccagcttactggggagcagtgggcctccagg
gagcagctcctcctccagctcccggagccagtcggcagcg
gtcaccccgtcatccaccacctcttccacccgtgccaccc
cagccccttctgctccagcagctgcctcagcaactagccc
gagccccgcgcccagttccgggaatggagccagcacagca
gccagcccgacccagcccatccagctgagcgacctccaga
gcatcctggccacgatgaacgtaccagccgggccagcagg
cggccagcaagtggacctggccagtgtgctgacgccggag
ataatggctcccatcctcgccaacgcggatgtccaggagc
gcctgcttccctacttgccatctggggagtcgctgccgca
gaccgcggatgagatccagaataccctgacctcgccccag
ttccagcaggccctgggcatgttcagcgcagccttggcct
cggggcagctgggccccctcatgtgccagttcggtctgcc
tgcagaggctgtggaggccgccaacaagggcgatgtggaa
gcgtttgccaaagccatgcagaacaacgccaagcccgagc
agaaagagggcgacacgaaggacaagaaggacgaagagga
ggacatgagcctggactgagccacgcgccgtcctccgagg
aactgggcgcttgcagtgcgttgcacaccctcacctccca
cccactgattattaataaagtcttttcttttacctgccaa
aaaaaaaaaaaaaaaa
CDK4 NM_000075.3 cacctcctgtccgcccctcagcgcatgggtggcggtcacg 2
tgcccagaacgtccggcgttcgccccgccctcccagtttc
cgcgcgcctctttggcagctggtcacatggtgagggtggg
ggtgagggggcctctctagcttgcggcctgtgtctatggt
cgggccctctgcgtccagctgctccggaccgagctcgggt
gtatggggccgtaggaaccggctccggggccccgataacg
ggccgcccccacagcaccccgggctggcgtgagggtctcc
cttgatctgagaatggctacctctcgatatgagccagtgg
ctgaaattggtgtcggtgcctatgggacagtgtacaaggc
ccgtgatccccacagtggccactttgtggccctcaagagt
gtgagagtccccaatggaggaggaggtggaggaggccttc
ccatcagcacagttcgtgaggtggctttactgaggcgact
ggaggcttttgagcatcccaatgttgtccggctgatggac
gtctgtgccacatcccgaactgaccgggagatcaaggtaa
ccctggtgtttgagcatgtagaccaggacctaaggacata
tctggacaaggcacccccaccaggcttgccagccgaaacg
atcaaggatctgatgcgccagtttctaagaggcctagatt
tccttcatgccaattgcatcgttcaccgagatctgaagcc
agagaacattctggtgacaagtggtggaacagtcaagctg
gctgactttggcctggccagaatctacagctaccagatgg
cacttacacccgtggttgttacactctggtaccgagctcc
cgaagttcttctgcagtccacatatgcaacacctgtggac
atgtggagtgttggctgtatctttgcagagatgtttcgtc
gaaagcctctcttctgtggaaactctgaagccgaccagtt
gggcaaaatctttgacctgattgggctgcctccagaggat
gactggcctcgagatgtatccctgccccgtggagcctttc
cccccagagggccccgcccagtgcagtcggtggtacctga
gatggaggagtcgggagcacagctgctgctggaaatgctg
acttttaacccacacaagcgaatctctgcctttcgagctc
tgcagcactcttatctacataaggatgaaggtaatccgga
gtgagcaatggagtggctgccatggaaggaagaaaagctg
ccatttcccttctggacactgagagggcaatctttgcctt
tatctctgaggctatggagggtcctcctccatctttctac
agagattactttgctgccttaatgacattcccctcccacc
tctccttttgaggcttctccttctccttcccatttctcta
cactaaggggtatgttccctcttgtccctttccctacctt
tatatttggggtccttttttatacaggaaaaacaaaacaa
agaaataatggtcttttttttttttttaatgtttcttcct
ctgtttggctttgccattgtgcgatttggaaaaaccactt
ggaagaagggactttcctgcaaaaccttaaagactggtta
aattacagggcctaggaagtcagtggagccccttgactga
caaagcttagaaaggaactgaaattgcttctttgaatatg
gattttaggcggggcgtggtggctcacgcctataatccca
gcacgttgggaggccaacgcgggtggatcacctgaggtca
ggagttcgagaccagcctgactaacatggtgaaaccctgt
ctctactaaaaatacaaaattagtcaggcgtggtggtgca
cacctgtaatcccagctacttgggagactgaggcaggagg
atcgcttgaacccgggaggcagaggttgcggtgagccgag
atcatgccattgcactccagcctgggcaacagagcaagac
tctgtgtcaaaaaaaaaaaaagaatatagatttttaaatg
gcaaaaaaaaaaaaaaaaaa
COMT NM_000754.3 cggcctgcgtccgccaccggaagcgccctcctaatccccg 3
cagcgccaccgccattgccgccatcgtcgtggggcttctg
gggcagctagggctgcccgccgcgctgcctgcgccggacc
ggggcgggtccagtcccgggcgggccgtcgcgggagagaa
ataacatctgctttgctgccgagctcagaggagaccccag
acccctcccgcagccagagggctggagcctgctcagaggt
gctttgaagatgccggaggccccgcctctgctgttggcag
ctgtgttgctgggcctggtgctgctggtggtgctgctgct
gcttctgaggcactggggctggggcctgtgccttatcggc
tggaacgagttcatcctgcagcccatccacaacctgctca
tgggtgacaccaaggagcagcgcatcctgaaccacgtgct
gcagcatgcggagcccgggaacgcacagagcgtgctggag
gccattgacacctactgcgagcagaaggagtgggccatga
acgtgggcgacaagaaaggcaagatcgtggacgccgtgat
tcaggagcaccagccctccgtgctgctggagctgggggcc
tactgtggctactcagctgtgcgcatggcccgcctgctgt
caccaggggcgaggctcatcaccatcgagatcaaccccga
ctgtgccgccatcacccagcggatggtggatttcgctggc
gtgaaggacaaggtcacccttgtggttggagcgtcccagg
acatcatcccccagctgaagaagaagtatgatgtggacac
actggacatggtcttcctcgaccactggaaggaccggtac
ctgccggacacgcttctcttggaggaatgtggcctgctgc
ggaaggggacagtgctactggctgacaacgtgatctgccc
aggtgcgccagacttcctagcacacgtgcgcgggagcagc
tgctttgagtgcacacactaccaatcgttcctggaataca
gggaggtggtggacggcctggagaaggccatctacaaggg
cccaggcagcgaagcagggccctgactgcccccccggccc
ccctctcgggctctctcacccagcctggtactgaaggtgc
cagacgtgctcctgctgaccttctgcggctccgggctgtg
tcctaaatgcaaagcacacctcggccgaggcctgcgccct
gacatgctaacctctctgaactgcaacactggattgttct
tttttaagactcaatcatgacttctttactaacactggct
agctatattatcttatatactaatatcatgttttaaaaat
ataaaatagaaattaagaatctaaatatttagatataact
cgacttagtacatccttctcaactgccattcccctgctgc
ccttgacttgggcaccaaacattcaaagctccccttgacg
gacgctaacgctaagggcggggcccctagctggctgggtt
ctgggtggcacgcctggcccactggcctcccagccacagt
ggtgcagaggtcagccctcctgcagctaggccaggggcac
ctgttagccccatggggacgactgccggcctgggaaacga
agaggagtcagccagcattcacacctttctgaccaagcag
gcgctggggacaggtggaccccgcagcagcaccagcccct
ctgggccccatgtggcacagagtggaagcatctccttccc
tactccccactgggccttgcttacagaagaggcaatggct
cagaccagctcccgcatccctgtagttgcctccctggccc
atgagtgaggatgcagtgctggtttctgcccacctacacc
tagagctgtccccatctcctccaaggggtcagactgctag
ccacctcagaggctccaagggcccagttcccaggcccagg
acaggaatcaaccctgtgctagctgagttcacctgcaccg
agaccagcccctagccaagattctactcctgggctcaagg
cctggctagcccccagccagcccactcctatggatagaca
gaccagtgagcccaagtggacaagtttggggccacccagg
gaccagaaacagagcctctgcaggacacagcagatgggca
cctgggaccacctccacccagggccctgccccagacgcgc
agaggcccgacacaagggagaagccagccacttgtgccag
acctgagtggcagaaagcaaaaagttcctttgctgcttta
atttttaaattttcttacaaaaatttaggtgtttaccaat
agtcttattttggcttatttttaa
DHCR7 NM_001163817.1 aatcgctgacatcatccgggggcgggcgcccctgccctgc 4
gggtgactccgacccctggctagagggtaggcggcgtgga
gcagcgcgcgcaagcgaggccaggggaaggtgggcgcagg
actttagccggttgagaaggatcaagcaggcatttggagc
acaggtgtctagaaacttttaaggggccggttcaagaagg
aaaagttcccttctgctgtgaaactatttggcaagaggct
ggagggcccaatggctgcaaaatcgcaacccaacattccc
aaagccaagagtctagatggcgtcaccaatgacagaaccg
catctcaagggcagtggggccgtgcctgggaggtggactg
gttttcactggcgagcgtcatcttcctactgctgttcgcc
cccttcatcgtctactacttcatcatggcttgtgaccagt
acagctgcgccctgactggccctgtggtggacatcgtcac
cggacatgctcggctctcggacatctgggccaagactcca
cctataacgaggaaagccgcccagctctataccttgtggg
tcaccttccaggtgcttctgtacacgtctctccctgactt
ctgccataagtttctacccggctacgtaggaggcatccag
gagggggccgtgactcctgcaggggttgtgaacaagtatc
agatcaatggcctgcaagcctggctcctcacgcacctgct
ctggtttgcaaacgctcatctcctgtcctggttctcgccc
accatcatcttcgacaactggatcccactgctgtggtgcg
ccaacatccttggctatgccgtctccaccttcgccatggt
caagggctacttcttccccaccagcgccagagactgcaaa
ttcacaggcaatttcttttacaactacatgatgggcatcg
agtttaaccctcggatcgggaagtggtttgacttcaagct
gttcttcaatgggcgccccgggatcgtcgcctggaccctc
atcaacctgtccttcgcagcgaagcagcgggagctccaca
gccatgtgaccaatgccatggtcctggtcaacgtcctgca
ggccatctacgtgattgacttcttctggaacgaaacctgg
tacctgaagaccattgacatctgccatgaccacttcgggt
ggtacctgggctggggcgactgtgtctggctgccttatct
ttacacgctgcagggtctgtacttggtgtaccaccccgtg
cagctgtccaccccgcacgccgtgggcgtcctgctgctgg
gcctggtgggctactacatcttccgggtggccaaccacca
gaaggacctgttccgccgcacggatgggcgctgcctcatc
tggggcaggaagcccaaggtcatcgagtgctcctacacat
ccgccgatgggcagaggcaccacagcaagctgctggtgtc
gggcttctggggcgtggcccgccacttcaactacgtcggc
gacctgatgggcagcctggcctactgcctggcctgtggcg
gcggccacctgctgccctacttctacatcatctacatggc
catcctgctgacccaccgctgcctccgggacgagcaccgc
tgcgccagcaagtacggccgggactgggagcgctacaccg
ccgcagtgccttaccgcctgctgcctggaatcttctaagg
gcacgccctagggagaagccctgtggggctgtcaagagcg
tgttctgccaggtccatgggggctggcatcccagctccaa
ctcgaggagcctcagtttcctcatctgtaaactggagaga
gcccagcacttggcaggtgtccagtacctaatcacgctct
gttccttgcttttgccttcaagggaattccgagtgtccag
cactgccgtattgccagcacagacggattttctctaatca
gtgtccctggggcaggaggatgacccagtcacctttacta
gtcctttggagacaatttacctgtattaggagcccaggcc
acgctacactctgcccacactggtgagcaggaggtcttcc
cacgccctgtcattaggctgcatttactcttgctaaataa
aagtgggagtggggcgtgcgcgttatccatgtattgcctt
tcagctctagatccccctcccctgcctgctctgcagtcgt
gggtggggcccgtgcgccgtttctccttggtagcgtgcac
ggtgttgaactgggacactggggagaaaggggctttcatg
tcgtttccttcctgctcctgctgcacagctgccaggagtg
ctctgcctggagtctgcagacctcagagaggtcccagcac
cggctgtggcctttcaggtgtaggcaggtgggctctgctt
cccgattccctgtgagcgcccaccctctcgaaagaatttt
ctgcttgccctatgactgtgcagactctggctcgagcaac
ccggggaacttcaccctcaggggcctcccacaccttctcc
agcgaggaggtctcagtcccagcctcgggagggcacctcc
ttttctgtgctttcttccctgaggcattcttcctcatccc
tagggtgttgtgtagaactctttttaaactctatgctccg
agtagagttcatctttatattaaactteccctgttcaaat
aa
HMOX2 NM_001127204.1 catctctaggccccgccccgcgctgcgtgcccacgttgcg 5
ccggcctcgcgccagtccgctgggctgcagggactgcggc
gcctgagggagtcgctgacgggcacgctgactggaggctg
gcggacaggcgacagcgacctgcggcagagtcttgctgcg
acacccaggctggagtgcaatggcgctatctcggctcact
gcaacctccgcttcccggattcaagcgattctcctgcctc
agcctcccgagtaggtgggactacaggaccagaggagcga
gagcagcaagaaccacacccagcagcaatgtcagcggaag
tggaaacctcagagggggtagacgagtcagaaaaaaagaa
ctctggggccctagaaaaggagaaccaaatgagaatggct
gacctctcggagctcctgaaggaagggaccaaggaagcac
acgaccgggcagaaaacacccagtttgtcaaggacttctt
gaaaggcaacattaagaaggagctgtttaagctggccacc
acggcactttacttcacatactcagccctcgaggaggaaa
tggagcgcaacaaggaccatccagcctttgcccctttgta
cttccccatggagctgcaccggaaggaggcgctgaccaag
gacatggagtatttctttggtgaaaactgggaggagcagg
tgcagtgccccaaggctgcccagaagtacgtggagcggat
ccactacatagggcagaacgagccggagctactggtggcc
catgcatacacccgctacatgggggatctctcggggggcc
aggtgctgaagaaggtggcccagcgagcactgaaactccc
cagcacaggggaagggacccagttctacctgtttgagaat
gtggacaatgcccagcagttcaagcagctctaccgggcca
ggatgaacgccctggacctgaacatgaagaccaaagagag
gatcgtggaggaggccaacaaggcttttgagtataacatg
cagatattcaatgaactggaccaggccggctccacactgg
ccagagagaccttggaggatgggttccctgtacacgatgg
gaaaggagacatgcgtaaatgccctttctacgctgctgaa
caagacaaaggtgccctggagggcagcagctgtcccttcc
gaacagctatggctgtgctgaggaagcccagcctccagtt
catcctggccgctggtgtggccctagctgctggactcttg
gcctggtactacatgtgaagcacccatcatgccacaccgg
taccctcctcccgactgaccactggcctacccctttctcc
agccctgactaaactaccacctcaggtgactttttaaaaa
atgctgggtttaagaaaggcaaccaataaaagccagatgc
tagagcctctgcctgacagcatcctctctatgggccatat
tccgcactgggcacaggccgtcaccctgggagcagtcggc
acagtgcagcaagcctggcccccgacccagctctactcca
ggcttccacacttctgggccctaggctgcttccggtagtc
cctgtttttgcagtacatgggtgactatctcccctgttgg
aggtgagtggcctgtaagtccaagctgtgcgagggggcct
tgctggatgctgctgtacaacttctgggcctctcttggac
cctgggagtgagggtgggtgtgggtggaagcctcagaggc
cttgggagctcatccctctcacccagaatccctctaaccc
cttgggtgcggtttgctcagccccagcttatctcctcctc
cgcgctgtgtaaatgctccagcactcaataaagtgggctt
tgcaagctaaaaaaaaaaaaaaaaaaaaaaaa
MCM2 NM_004526.3 atgacgtcgcgttccgtagggctcttcccgggctttggtg 6
ggtcacgtgaaccacttttcgcgcgaaacctggttgttgc
tgtagtggcggagaggatcgtggtactgctatggcggaat
catcggaatccttcaccatggcatccagcccggcccagcg
tcggcgaggcaatgatcctctcacctccagccctggccga
agctcccggcgtactgatgccctcacctccagccctggcc
gtgaccttccaccatttgaggatgagtccgaggggctcct
aggcacagaggggcccctggaggaagaagaggatggagag
gagctcattggagatggcatggaaagggactaccgcgcca
tcccagagctggacgcctatgaggccgagggactggctct
ggatgatgaggacgtagaggagctgacggccagtcagagg
gaggcagcagagcgggccatgcggcagcgtgaccgggagg
ctggccggggcctgggccgcatgcgccgtgggctcctgta
tgacagcgatgaggaggacgaggagcgccctgcccgcaag
cgccgccaggtggagcgggccacggaggacggcgaggagg
acgaggagatgatcgagagcatcgagaacctggaggatct
caaaggccactctgtgcgcgagtgggtgagcatggcgggc
ccccggctggagatccaccaccgcttcaagaacttcctgc
gcactcacgtcgacagccacggccacaacgtcttcaagga
gcgcatcagcgacatgtgcaaagagaaccgtgagagcctg
gtggtgaactatgaggacttggcagccagggagcacgtgc
tggcctacttcctgcctgaggcaccggcggagctgctgca
gatctttgatgaggctgccctggaggtggtactggccatg
taccccaagtacgaccgcatcaccaaccacatccatgtcc
gcatctcccacctgcctctggtggaggagctgcgctcgct
gaggcagctgcatctgaaccagctgatccgcaccagtggg
gtggtgaccagctgcactggcgtcctgccccagctcagca
tggtcaagtacaactgcaacaagtgcaatttcgtcctggg
tcctttctgccagtcccagaaccaggaggtgaaaccaggc
tcctgtcctgagtgccagtcggccggcccctttgaggtca
acatggaggagaccatctatcagaactaccagcgtatccg
aatccaggagagtccaggcaaagtggcggctggccggctg
ccccgctccaaggacgccattctcctcgcagatctggtgg
acagctgcaagccaggagacgagatagagctgactggcat
ctatcacaacaactatgatggctccctcaacactgccaat
ggcttccctgtctttgccactgtcatcctagccaaccacg
tggccaagaaggacaacaaggttgctgtaggggaactgac
cgatgaagatgtgaagatgatcactagcctctccaaggat
cagcagatcggagagaagatctttgccagcattgctcctt
ccatctatggtcatgaagacatcaagagaggcctggctct
ggccctgttcggaggggagcccaaaaacccaggtggcaag
cacaaggtacgtggtgatatcaacgtgctcttgtgcggag
accctggcacagcgaagtcgcagtttctcaagtatattga
gaaagtgtccagccgagccatcttcaccactggccagggg
gcgtcggctgtgggcctcacggcgtatgtccagcggcacc
ctgtcagcagggagtggaccttggaggctggggccctggt
tctggctgaccgaggagtgtgtctcattgatgaatttgac
aagatgaatgaccaggacagaaccagcatccatgaggcca
tggagcaacagagcatctccatctcgaaggctggcatcgt
cacctccctgcaggctcgctgcacggtcattgctgccgcc
aaccccataggagggcgctacgacccctcgctgactttct
ctgagaacgtggacctcacagagcccatcatctcacgctt
tgacatcctgtgtgtggtgagggacaccgtggacccagtc
caggacgagatgctggcccgcttcgtggtgggcagccacg
tcagacaccaccccagcaacaaggaggaggaggggctggc
caatggcagcgctgctgagcccgccatgcccaacacgtat
ggcgtggagcccctgccccaggaggtcctgaagaagtaca
tcatctacgccaaggagagggtccacccgaagctcaacca
gatggaccaggacaaggtggccaagatgtacagtgacctg
aggaaagaatctatggcgacaggcagcatccccattacgg
tgcggcacatcgagtccatgatccgcatggcggaggccca
cgcgcgcatccatctgcgggactatgtgatcgaagacgac
gtcaacatggccatccgcgtgatgctggagagcttcatag
acacacagaagttcagcgtcatgcgcagcatgcgcaagac
ttttgcccgctacctttcattccggcgtgacaacaatgag
ctgttgctcttcatactgaagcagttagtggcagagcagg
tgacatatcagcgcaaccgctttggggcccagcaggacac
tattgaggtccctgagaaggacttggtggataaggctcgt
cagatcaacatccacaacctctctgcattttatgacagtg
agctcttcaggatgaacaagttcagccacgacctgaaaag
gaaaatgatcctgcagcagttctgaggccctatgccatcc
ataaggattccttgggattctggtttggggtggtcagtgc
cctctgtgctttatggacacaaaaccagagcacttgatga
actcggggtactagggtcagggcttatagcaggatgtctg
gctgcacctggcatgactgtttgtttctccaagcctgctt
tgtgcttctcacctttgggtgggatgccttgccagtgtgt
cttacttggttgctgaacatcttgccacctccgagtgctt
tgtctccactcagtaccttggatcagagctgctgagttca
ggatgcctgcgtgtggtttaggtgttagccttcttacatg
gatgtcaggagagctgctgccctcttggcgtgagttgcgt
attcaggctgcttttgctgcctttggccagagagctggtt
gaagatgtttgtaatcgttttcagtctcctgcaggtttct
gtgcccctgtggtggaagagggcacgacagtgccagcgca
gcgttctgggctcctcagtcgcaggggtgggatgtgagtc
atgcggattatccactcgccacagttatcagctgccattg
ctccctgtctgtttccccactctcttatttgtgcattcgg
tttggtttctgtagttttaatttttaataaagttgaataa
aatataaaaaaaaaaaaaaaaaaa
PDXK NM_003681.4 cggaactcgcgggttcggagccgcccgctgaggtcagaag 7
gaggcgtctgcgctgatcgggtccgccgcgcgccagagcc
agagtcgcagccgaggggagccggggccggagcccgagcc
cgagccgagccggagcccgagcgagcggcggagaccgtgc
ccccgcctcggccccgcgccgccgcggccaggcccggcat
ggaggaggagtgccgggtgctctccatacagagccacgtc
atccgcggctacgtgggcaaccgggcggccacgttcccgc
tgcaggttttgggatttgagattgacgcggtgaactctgt
ccagttttcaaaccacacaggctatgcccactggaagggc
caagtgctgaattcagatgagctccaggagttgtacgaag
gcctgaggctgaacaacatgaataaatatgactacgtgct
cacaggttatacgagggacaagtcgttcctggccatggtg
gtggacattgtgcaggagctgaagcagcagaaccccaggc
tggtgtacgtgtgtgatccagtcttgggtgacaagtggga
cggcgaaggctcgatgtacgtcccggaggacctccttccc
gtctacaaagaaaaagtggtgccgcttgcagacattatca
cgcccaaccagtttgaggccgagttactgagtggccggaa
gatccacagccaggaggaagccttgcgggtgatggacatg
ctgcactctatgggccccgacaccgtggtcatcaccagct
ccgacctgccctccccgcagggcagcaactacctgattgt
gctggggagtcagaggaggaggaatcccgctggctccgtg
gtgatggaacgcatccggatggacattcgcaaagtggacg
ccgtctttgtgggcactggggacctgtttgctgccatgct
cctggcgtggacacacaagcaccccaataacctcaaggtg
gcctgtgagaagaccgtgtctaccttgcaccacgttctgc
agaggaccatccagtgtgcaaaagcccaggccggggaagg
agtgaggcccagccccatgcagctggagctgcggatggtg
cagagcaaaagggacatcgaggacccagagatcgtcgtcc
aggccacggtgctgtgagggccccgccgcttgcccgtgac
acgcagcgcgttggtgtctccgtgtttgtccctgtgaaaa
catgtaacgtctgccttagagccatgaccgaaacttgata
tttttttctttcatgagtgtccggcatctgctggtcttca
ttgtgaaacgtgccagtcgtgctttgtgaaaaataacaaa
gtggtcacagaaatttgtgatctgaaaacccggctccctt
ccccacaaggctcctgggcctccgggaagacgggcccctg
tttgccatctcgggggtgttccctgtgggagggtgagtgg
gtgaggccgagcctgctgcgtgtggagcctcgagtgggcc
ctggctgccactaccgtacagaggccgtgtcgcgctgggc
tgggcctgggtggcctctgtctttgcatctctgagaagga
gtcgggtggtaacggttggggtcaggaagaattctgccaa
gtatctttactgtcattctgaccatagcctctttgttccc
gcattcgaacttttggttcttactttgctgctcgtttagt
ccctggggatttcagatcttaggctgttgtttcaccgtat
gggagggttgatgtgagcttgcttggagacacacggtgca
gcatcagggaccttcccaggccccagcaaattcaagtcgg
tctgcagacctctcagctacccgcgggacctcttgtaacc
catcggcatcttccaggaatccgccgagtgacttgaggaa
gatgctaacgcagtaaggtctgtgctgggccaagagcagc
tttgaagctccagagaaccaccccgtcaggttccttgtgg
aagctcccctcatccgtggtgcagcaggctgagcactgcg
cgtttgccacgtgctgcccgtgacagcacattgagccaca
gcatttgtagacaggacagaggggtgcctgccccctgccc
ctgctggcacatttaacccttgtcccctgacctcagttct
gtgccccaccaaatgcccaggggcaagaggccaccctgga
agctgccaatcttccaaggtgggtgtggggcacggtgggg
gcgggcagctcccaggcccttgggcaggctggggtgacgg
cagaggccacagcaccagctctgacaagtcctatcatcct
ctgctcagcagtgacctccctggccccactttgcccagag
tttggggtccccccaggtatagctataggcggcagtgcct
gtccctggcctgccttgatttcagccacacccctgcagcc
ctgcatcccagctctggggtgtgcagaggtttgtgtctcc
agggaacccacggctggagagaaatagggagatgcaggaa
gtgggggcccatggggcccccaagaagcggactctccaag
gggtacccccaccccgctaccttccccacggacgggcccc
tcctggagcccataccctcctgtgaggccattccagtgtc
ttctagaaagactcgcttgccaggagtgcgttctttgttg
aaaaatgccctgaagcgaaaagatgcaggtttatatggaa
cccccaccccctcccccactctcccactctgttcgttctg
aatgtcttcacgagcgtgcatcagggcgcctggctccccc
acctcagccagtgagtcagacacgggtttcgcagccatgt
ttcctggctccgaggacacgggtggcaggcccgttgcagc
ccagagccactggtccctacagggcgccgccacaccagca
ggaaggaggatggctgtgtccggagcctggcggggaggcg
gcctccccagtatgtgagtgcagggatctgccagaaccac
ctggccctctgtagggcgtttaactggaaataccctcact
gccaagtggagactggggcgtgtgccacattgccagccac
caggaaagcttttctttttcttttttttttttttttaaac
accaagagcacgtatagcatgggggaaagaacctaaatgt
ctctctgtcctgtgagctggtgaaaaacccagcatgagaa
cgcagtgtcaggtgtgggactccttctgcccctgcagtgg
gtgttacgggcggtgtgccctggcgagcaagctttgattc
ttggttctttgagctcgtttcagaggctgagtccccacat
cagctttagttcttggacttccctgtattaagcaagaatt
aggagaatggctgtccctgcaggcgcctcccgtaaatcct
gagctctctggcgcaatctgaaacttctcttctgttttct
ttggctgtatcagccgaaccaggagaggcctgggctgcga
ctaaggagaaagaaatcgggggtttctgagagcagatggt
gcctttgtgggtgcagggcttttgtggaaattgtcagcct
ctacgggcagagtccggcatcccctccccagactgcctgc
tgtcaaaccacggagcagctggagcctgccctgtccacgg
cccgtttccacccgggcatgttcgtctctcatgacttcgg
cagaggcccctggtggccttcagtttcagtttctcatcca
ggaaggtaaccttgggcattggcagtgggtttccctatgg
cttggatccagattagaattgatctttgttttcactttcc
atagttaataacatgcaaaataatgagaagaatttatttt
aaggtgacagctatactggtccaacatcgcctgcttattg
tcagggtacagaagtttaatactttcttaatccagttttt
caaacttctccctgtagaccgtaaggatgaattccacaat
aggatcctttttaaaatcgattttaaattgttgcctagtc
ctgccaaggttattatgtgcatctgttatttttccaatac
atgtaaacagttgcagcatgatgctttgtttaatgtcctg
ttcttaagctcgttagagccagttttgaaacgtttggtct
taccgtgaacggaggctggcttggcttagccacgctgatg
agtaagtgagggatgtctccatcttgagatcaccaggcaa
gagagttgcctgcaccaggtaagaggccaaagcccctggg
gtaacagtccccaccgctacccgaggtaaaacaataaaag
ctatgtggttgagctcaggcctctcgtgcctggtgtcaga
gaaggcagagcccacagtaggtgcacggtgcaaggccctg
ggagggcactggccagggaaggtggtatagatggccctca
gattgcggggccccgagcagctccccactctgcccgtcca
ccttccctggctccagcctcattctctctttagtttaact
atgcaaagagaggaggttgagagtgttctggcagctggag
ctcttttccttgtccttcctgccctccgatggggccacct
gtgtcggggcagcagtgtccatgtttatggagatcagagg
tgtccccactgtgtggctggactgtactctgctgcccggg
tagccaggagtctctccctctctcccctgccgcctgcctg
gtctcatgggcctccttcacacacccctccctgtggatcg
cctgcctgggcccagagcaggggaactggagtttgtgagt
gagcagagcaggttatgtgcagacagggaaacgagaactt
tggacctggctttctgagtccaggtgagagctgtgtggcc
ccccgatgccactctgcccgccggagggatgtgcctgctg
agccttttccttccacgccgcctctcactgccaggccagc
ggcttccgctgagactcgctggagaggcggctcccgtgtc
cgtccaccgagcactcagatggatgctgatcaccagggcc
gagggggctcccagaaggaccccaggccctggggagggtg
gctgtgggaggccaagtccactgcccggaagtcttgtcag
ccctaagccagggaagcctggagcgtggcctggcgggtct
gggtggacaccgtccccactccggactcccagcacagggg
aggatacctgagcctgtatggccctgtagccctgggcaga
gctgggcctgtcgtgtgttcctgcctggcaggtgcaggtg
ctggccatctgcaggtggaaggaggtgggaatcttggatt
ttttgtttttttttgtttttttttttttgagatgaagtct
cgctctgacacccaggctggcgtgcagtggtgtgatctcg
gctcactgcaaactccgcttcctgggttcaagtggttctc
ctgccccagcctcccaagtagctgggattacaggcatgcg
ccaccacgctcagctgatttttgtatttttagtagagatg
gggtttcaccatgttggccaagctggtctcaaactcctga
cctcaagtgatctgcccgcctcggcctcccagagtgctgg
gattacaggcatgagccagtgcacccggcggaatcttgga
atttttatagacagcacctcagtttctgactccagccgca
cacctcctgcctctgccagcaggggttgccgccagaccag
agccagggccaggtccctgcgtccatcccccccggtagga
tggacgtgagccatccttctaggggacttttttcagtgtg
cgactcgtctctgttaggtggtaggagccagtttgtgtgg
cctgtgccacgctccacagtgcgtggctgggctctgtgtg
tggcctgtgtcccctgtccctgcaggacccagcaggcatc
gtggcgtgacagctgtgtccaagccactgcccgggcatcc
catcacccaccagggtgcacggtctctcctgctgggggct
ttctgtcgcatgtgtgtctcctgtcgactctgcagtttgt
tctcagagcagaatgtttcctgttctcagtgcacaaagac
actggttttcaatcggcgtctaaaaccacgttcctgcctt
tcattgcaacacggtgtgttcatttgtttaaaacagttta
atgagtaagtttagatgactggtcaatatcttaaaaatgt
atattagtaagaagttcttcctggaatttttctttcgatt
ctggcagaataaacaggtgtttttagttttcccactgtct
gagccaagcaggaccctgtcccagagcaagagatgtcccc
ttccatctctgacccttgcctgggacaagctttgatgggg
ggccccagcttcaaggctgtggtgggaacagcacccccaa
atgccagcctctcctttcttcccatccaccagtatactgc
ggggccatttctggtctttgtccaacaggaaacccatttc
tggtgggatatgccttccagtgccacagggccactcaccc
catgcatctctgtcctgcccgtcagtgctgggacggacag
caagggcaagcccagtgtctggcggataggtgggtgggaa
cagagaggggagaatgccgtcctaagcttctgcttgggga
tcccccacacgacctgggtactgcctgggaaacctgtcct
aagtaaaactatggacctcgcctcgcccaccggcctgcga
agccagcatctccgtgaaggtggatggaagcgcctttgtc
ctcattttgagctgcaagctgggtcagcggctctgaagcc
ctcgagtgactttctaacccaagacccagcccctggcagg
aggagggtgggtgcagggctggtgggacaaaaagaggcct
cagcaggcctggaagacccttccagtacatcccacagcgt
gtcgagcagctgggagaacctgtgtcaagctcgagccgtc
ataggtccccatgaggtgtctgaagccccttcttggtgat
gggaggcagaggtgctgacgttctggagcatggacgtgag
tcctcagctggctccgcgtgggcccttggagggtgccagg
tgtgtggtgaccttctggatgcctttaacttcatggctgc
gtcattcctgatttagaactttaaccggagcttcatctag
tgattgcaaaactggaccaatgggaggacggcggcgcagc
ccgctccctccgtggaatggagctcagctcttcggaggca
tcaaagcacctgtcgcctccgtggtccccctgctgaggga
gtgcggcctctgcaaggttcgggggtggcttcgtttgcct
ggagtggccggccctgcttgtgccatgtggatgtttgtga
gcctcggtcctacagcactgtgtaggctgcatctgtttcg
tgctggtcctgttgacttgtatgatatccacaaataaata
ttttcatggcggtcgtgttgaaaaaaaaaa
POP7 NM_005837.2 ggaaggggcggggcgaacggaagccgggaaggcgattcat 8
agctcgcggggtacgggcgcgcgtgcgcactccgcagccc
gttcaggaccccggcgcgggcagggcgcccacgagctggc
tggctgcttgcacccacatccttctttctctgggacctgg
ggtcgcggttacttgggctggccggcgaacccttgagtgg
cctggcggggagcgggcctcgcgcgcctggagggccctgt
ggaacgaagagaggcacacagcatggcagaaaaccgagag
ccccgcggtgctgtggaggctgaactggatccagtggaat
acacccttaggaaaaggcttcccagccgcctgccccggag
acccaatgacatttatgtcaacatgaagacggactttaag
gcccagctggcccgctgccagaagctgctggacggagggg
cccggggtcagaacgcgtgctctgagatctacattcacgg
cttgggcctggccatcaaccgcgccatcaacatcgcgctg
cagctgcaggcgggcagcttcgggtccttgcaggtggctg
ccaatacctccaccgtggagcttgttgatgagctggagcc
agagaccgacacacgggagccactgactcggatccgcaac
aactcagccatccacatccgagtcttcagggtcacaccca
agtaattgaaaagacactcctccacttatcccctccgtga
tatggctcttcgcatgctgagtactggacctcggaccaga
gccatgtaagaaaaggcctgttccctggaagcccaaagga
ctctgcattgagggtgggggtaattgtctcttggtgggcc
cagttagtgggccttcctgagtgtgtgtatgcggtctgta
actattgccatataaataaaaaatcctgttgcactagtgt
cctgccatcccaaaaaaaaaaaaaaaaaa
S100P NM_005980.2 tgaggctgccttataaagcaccaagaggctgccagtggga 9
cattttctcggccctgccagcccccaggaggaaggtgggt
ctgaatctagcaccatgacggaactagagacagccatggg
catgatcatagacgtcttttcccgatattcgggcagcgag
ggcagcacgcagaccctgaccaagggggagctcaaggtgc
tgatggagaaggagctaccaggcttcctgcagagtggaaa
agacaaggatgccgtggataaattgctcaaggacctggac
gccaatggagatgcccaggtggacttcagtgagttcatcg
tgttcgtggctgcaatcacgtctgcctgtcacaagtactt
tgagaaggcaggactcaaatgatgccctggagatgtcaca
gattcctggcagagccatggtcccaggcttcccaaaagtg
tttgttggcaattattcccctaggctgagcctgctcatgt
acctctgattaataaatgcttatgaaatga
SNRPA NM_004596.4 ggcggggccaggagagaaagctttgtggtttggtctcagg 10
gaagtagcaggcgccggttgagagaactacggccctgtcg
gaaggtaacctccggtgcaaacgaccatcggcggcaggcg
agcggtacgcttggcgtccgggccttcctgggcccgtctg
aggaaacttgctgctcgaggccaggctgcctaggacctgt
cccttttttctatactggctcccacatccgggttttttct
ccgggacggcccttcggatgcttgggccaatgggaatcgc
catttagggtgctccgcccaccgggtcgcgtagagcatcc
tggaagtcgtagtaaatctctcgagagttctctccgcacg
cgggctggagaagcgggtcctacgcacgctttgttgtcgc
gctttgcctccgtccttgcccctactcccgccttacctga
cttccttttcggaggaagatccttgagcagccgacgttgg
gacaaaggatttggagaaacccagggctaaagtcacgttt
ttcctcctttaagacttacctcaacacttcactccatggc
agttcccgagacccgccctaaccacactatttatatcaac
aacctcaatgagaagatcaagaaggatgagctaaaaaagt
ccctgtacgccatcttctcccagtttggccagatcctgga
tatcctggtatcacggagcctgaagatgaggggccaggcc
tttgtcatcttcaaggaggtcagcagcgccaccaacgccc
tgcgctccatgcagggtttccctttctatgacaaacctat
gcgtatccagtatgccaagaccgactcagatatcattgcc
aagatgaaaggcaccttcgtggagcgggaccgcaagcggg
agaagaggaagcccaagagccaggagaccccggccaccaa
gaaggctgtgcaaggcgggggagccacccccgtggtgggg
gctgtccaggggcctgtcccgggcatgccgccgatgactc
aggcgccccgcattatgcaccacatgccgggccagccgcc
ctacatgccgccccctggtatgatccccccgccaggcctt
gcacctggccagatcccaccaggggccatgcccccgcagc
agcttatgccaggacagatgccccctgcccagcctctttc
tgagaatccaccgaatcacatcttgttcctcaccaacctg
ccagaggagaccaacgagctcatgctgtccatgcttttca
atcagttccctggcttcaaggaggtccgtctggtacccgg
gcggcatgacatcgccttcgtggagtttgacaatgaggta
caggcaggggcagctcgcgatgccctgcagggctttaaga
tcacgcagaacaacgccatgaagatctcctttgccaagaa
gtagcaccttttccccccatgcctgccccttcccctgttc
tggggccacccctttcccccttggctcagccccctgaagg
taagtccccccttgggggccttcttggagccgtgtgtgag
tgagtggtcgccacacagcattgtacccagagtctgtccc
cagacattgcacctggcgctgttaggccggaattaaagtg
gctttttgaggtttggtttttcacaatcaaaaaaaaaaaa
aaaaaa
SORD NM_003104.5 ctccacgctagcgccgcccaggctggcacaaaggaggaag 11
cctagtcccgcccctgcgtgcggcgcttctcccaggcccc
accttccatccagtgccctggaccctcggctgggtagcgc
caccagagcgaccaaacgtcccgcgccttccaggccgcac
tccagagccaaaagagctccatggcggcggcggccaagcc
caacaacctttccctggtggtgcacggaccgggggacttg
cgcctggagaactatcctatccctgaaccaggcccaaatg
aggtcttgctgaggatgcattctgttggaatctgtggctc
agatgtccactactgggagtatggtcgaattgggaatttt
attgtgaaaaagcccatggtgctgggacatgaagcttcgg
gaacagtcgaaaaagtgggatcatcggtaaagcacctaaa
accaggtgatcgtgttgccatcgagcctggtgctccccga
gaaaatgatgaattctgcaagatgggccgatacaatctgt
caccttccatcttcttctgtgccacgccccccgatgacgg
gaacctctgccggttctataagcacaatgcagccttttgt
tacaagcttcctgacaatgtcacctttgaggaaggcgccc
tgatcgagccactttctgtggggatccatgcctgcaggag
aggcggagttaccctgggacacaaggtccttgtgtgtgga
gctgggccaatcgggatggtcactttgctcgtggccaaag
caatgggagcagctcaagtagtggtgactgatctgtctgc
tacccgattgtccaaagccaaggagattggggctgattta
gtcctccagatctccaaggagagccctcaggaaatcgcca
ggaaagtagaaggtcagctggggtgcaagccggaagtcac
catcgagtgcacgggggcagaggcctccatccaggcgggc
atctacgccactcgctctggtgggaacctcgtgcttgtgg
ggctgggctctgagatgaccaccgtacccctactgcatgc
agccatccgggaggtggatatcaagggcgtgtttcgatac
tgcaacacgtggccagtggcgatttcgatgcttgcgtcca
agtctgtgaatgtaaaacccctcgtcacccataggtttcc
tctggagaaagctctggaggcctttgaaacatttaaaaag
ggattggggttgaaaatcatgctcaagtgtgaccccagtg
accagaatccctgatgttaatgggctctgccctcatcccc
acagtcttgggatctcagggcacaatggctggacatgggt
gggctctgatgcagaactttctcttttgaatgttaagaat
aactaatacaattcattgtgaacagaagtccttaagcaga
ggaattggtgtgccttaaagatacaatctgggatagtttg
ggggaacttgtagccagaatgccctgttcatgctgagcaa
agttcagcaagtagagcagagtttggcaggcaggtgccag
gaactccccttcttcctggagtgccttcattgaggaagga
aatctggcccttgggtttcctggttccactgctactgacc
cagaggggaatgagggctgagttatgaaaagataacttca
tgaagacttaactggcccagaagctgattttcatgaaaat
ctgccactcagggtctgggatgaaggcttgtcagcacttc
cagtttagaacgcaatgtttctagagacatattggctgtt
tgttttgatgataaaaggagaataagaaaaggcatcactt
tcctggatccaggataatttttaaaccaatcaaatgaaaa
aaacaaacaaacaaaaaaggaaatgtcatgtgaggttaaa
ccagtttgcattcccctaatgtggaaaaagtaagaggact
actcagcactgtttgaagattgcctcttctacagcttctg
agaattgtgttatttcacttgccaagtgaaggaccccctc
cccaacatgccccagcccacccctaagcatggtcccttgt
caccaggcaaccaggaaactgctacttgtggacctcacca
gagaccaggagggtttggttagctcacaggacttccccca
ccccagaagattagcatcccatactagactcatactcaac
tcaactaggctcatactcaattgatggttattagacaatt
ccatttctttctggttattataaacagaaaatctttcctc
ttctcattaccagtaaaggctcttggtatctttctgttgg
aatgatttctatgaacttgtcttattttaatggtgggttt
tttttctggtaagatttagacctaaatcgcatcatgccaa
cttgtgactttgagactattcatcaagaatgaggatatag
tagccatgacatagcttgagctatagcctttaattcctta
ctttggctatgggtggagggtgagtttgaagaggttctga
ttttcttgtaacctgggaaagccatgaccttgtgcccgat
tctttcagattgctttgggtaataaatattggtggtggta
tctgactcatgctgctgtttatggtcctgtttagtgggga
atggactcaggttacccatttcccagagggaaggatccca
ggatttttgaaggttacatattttctgtaccaaatataat
ttcattgacatgaattatctctaatcctcatgacaagcca
catacacaatcattttgtagataaagaagatataaatgcc
agaggagaccttaagattgtcttacaacacaacccttcag
ttaacgagagagg
STOML2 NM_001287031.1 tccgggggagcggaactgcaagaggaaaggctcgggtagg 12
cttctgggagcgaccgctccgctcgtctcgttggttccgg
aggtcgctgcggcggtgggaaatgctggcgcgcgcggcgc
ggggcactggggcccttttgctgaggggctctctactggc
ttctggccgcgctccgcgccgcgcctcctctggattgccc
cgaaacaccgtggtactgttcgtgccgcagcaggaggcct
gggtggtggagcgaatgggccgattccaccggatcctgga
gcctggtttgaacatcctcatccctgtgttagaccggatc
cgatatgtgcagagtctcaaggaaattgtcatcaacgtgc
ctgagcagtcggctgtgactctcgacaatgtaactctgca
aatcgatggagtcctttacctgcgcatcatggacccttac
aaggcaagctacggtgtggaggaccctgagtatgccgtca
cccagctagctcaaacaaccatgagatcagagctcggcaa
actctctctggacaaagtcttccgggtggaggcagagcgg
cggaaacgggccacagttctagagtctgaggggacccgag
agtcggccatcaatgtggcagaagggaagaaacaggccca
gatcctggcctccgaagcagaaaaggctgaacagataaat
caggcagcaggagaggccagtgcagttctggcgaaggcca
aggctaaagctgaagctattcgaatcctggctgcagctct
gacacaacataatggagatgcagcagcttcactgactgtg
gccgagcagtatgtcagcgcgttctccaaactggccaagg
actccaacactatcctactgccctccaaccctggcgatgt
caccagcatggtggctcaggccatgggtgtatatggagcc
ctcaccaaagccccagtgccagggactccagactcactct
ccagtgggagcagcagagatgtccagggtacagatgcaag
tcttgatgaggaacttgatcgagtcaagatgagttagtgg
agctgggcttggccagggagtctgggaacaaggaagcaga
ttttcctgattctggctctagcttccctgccaagattttg
gtttttatttttttatttgaactttagtcgtgtaataaac
tcaccagtggcaaaccagaaactgtcctctttgattgggg
aatgaagttgggaaagtcactagcattttccttggatcca
gtcctgtcagcatgatgcctccatgaataagagtgaactt
cttgtaaagtgaaact
UMPS NM_000373.3 ctgcagacgaggcaggcggaagaggcgggacttcgcgggt 13
gacgtcatcggggcgccggaggcccggggcgcctgggaat
ttgaagcaaacaggcagcgcgcgacaatggcggtcgctcg
tgcagctttggggccattggtgacgggtctgtacgacgtg
caggctttcaagtttggggacttcgtgctgaagagcgggc
tttcctcccccatctacatcgatctgcggggcatcgtgtc
tcgaccgcgtcttctgagtcaggttgcagatattttattc
caaactgcccaaaatgcaggcatcagttttgacaccgtgt
gtggagtgccttatacagctttgccattggctacagttat
ctgttcaaccaatcaaattccaatgcttattagaaggaaa
gaaacaaaggattatggaactaagcgtcttgtagaaggaa
ctattaatccaggagaaacctgtttaatcattgaagatgt
tgtcaccagtggatctagtgttttggaaactgttgaggtt
cttcagaaggagggcttgaaggtcactgatgccatagtgc
tgttggacagagagcagggaggcaaggacaagttgcaggc
gcacgggatccgcctccactcagtgtgtacattgtccaaa
atgctggagattctcgagcagcagaaaaaagttgatgctg
agacagttgggagagtgaagaggtttattcaggagaatgt
ctttgtggcagcgaatcataatggttctcccctttctata
aaggaagcacccaaagaactcagcttcggtgcacgtgcag
agctgcccaggatccacccagttgcatcgaagcttctcag
gcttatgcaaaagaaggagaccaatctgtgtctatctgct
gatgtttcactggccagagagctgttgcagctagcagatg
ctttaggacctagtatctgcatgctgaagactcatgtaga
tattttgaatgattttactctggatgtgatgaaggagttg
ataactctggcaaaatgccatgagttcttgatatttgaag
accggaagtttgcagatataggaaacacagtgaaaaagca
gtatgaaggaggtatctttaaaatagcttcctgggcagat
ctagtaaatgctcacgtggtgccaggctcaggagttgtga
aaggcctgcaagaagtgggcctgcctttgcatcgggggtg
cctccttattgcggaaatgagctccaccggctccctggcc
actggggactacactagagcagcggttagaatggctgagg
agcactctgaatttgttgttggttttatttctggctcccg
agtaagcatgaaaccagaatttcttcacttgactccagga
gttcagttggaagcaggaggagataatcttggccaacagt
acaatagcccacaagaagttattggcaaacgaggttccga
tatcatcattgtaggtcgtggcataatctcagcagctgat
cgtctggaagcagcagagatgtacagaaaagctgcttggg
aagcgtatttgagtagacttggtgtttgagtgcttcagat
acatttttcagatacaatgtgaagacattgaagatatgtg
gtcctcctgaaagtcactggctggaaataatccaattatt
cctgcttggattcttccacagggcctgtgtaagaatgggt
tctggagttctcatggtctttaggaaatattgagtaattt
gtaatcaccgcattgatactataataagttcattcttaag
cttgctttttttgagactggtgtttgttagacagccacag
tcctgtctgggttagggtcttccacatttgaggatccttc
ctatctctccatgggactagactgctttgttattctattt
attttttaatttttttcgagacaggatctcactctgttgc
ccaggatggagtgcagtggtgagatcacggctcattgcag
cctcgacctcccaggtgatcctcccacctcagcttccaga
ttagctggtgctataggcatgcaccaccacgtccatctaa
atttctttattatttgtagagatgaggtcttgccatgtta
cccaggctggtctcaactcctgggctcaagcgatcctcct
gcctcagtctctcaaagtgctgggattacaggtgtgagcc
actgtgcccagcctaattgcagtaagacaaaaattctagg
gcaccaagaggctaaagtcagcacagcttttcttgtgtcc
tgtattctctgtctaatgtgttgcccaaataatacctaat
tgttagccattcccctccatctctggcctaaaagtgatag
tccaggtatccacatgggctggttcccagaactgccattg
ctcactctccaaagaggggaaggtggggaaggggaaggtg
actatagctcagctcctgagctagtatctggctgttattt
caacaaccggagttggggtttgggctcattttttccccta
gccagcaattatggaccagtagtaacacaagtgacagctt
cctgtgactgacttcacaattaggaggtctaagattccat
ttgggtatttgcttaaggatcccacataattgtcccaacg
gtcattagtagaggggaggtaagccttcattaataataaa
gagaaagcccacattcaaggtggtgtttgagcaggggcag
ggtgagggctgtcccggtgctcattgcaccagcacactca
cattccttctcatttggggcccacctgcaggaagtggcac
aggatcagccatttccccacccttgtcagctgatggccca
ctgttctttaatgactcagaggaatgcctaggattttttt
ttttttttgagacagaatctcactgtcgcccaggctggag
ttcagtggcacgatctcggctcactgcaacttctgcctct
ctggttcaagcagttctcctgcctcagcctcccgagtagc
tgggactacaagcctaggatttttaactcaggtttttatt
atattccctcctgaagtttttacttcaagagcttctgctc
taaagtccaatttgggcttcatgtccccagtgctgcatct
ccagggaaatgctgtctgtgggagagaccaactctcaagg
aagaagtggccacagaaggagcaggaagggagttggccct
cagggctactctggggaagccaaaagtcatgaaggggaga
agaattttctgacaaaaacttgcaggaatctcttaggtgt
cttcagtgttggagtgatatgttgagaggcctttggagtg
atgtgctgaggtctcaggcgcccacctccctggctgtcac
ttccatgtgtcagtggttctcccactttagcaggtatcag
agtcacctggagtcttgtcaaaacaggtaccagccccacc
cgcagcgtttctgactctgggtagctctgggatggggctt
gagaatttgcgtttccaaaaaggtcccaggtgatgctgcg
gttgcctgcgcagggactggactttgagaaccacttcact
ggttattcacatttctgcctctgcagtgagacagccttga
ggtctgcctcctgctaagagtcacatgctcctgtccttta
gaaatgtgggctcctgccatctccaggacgcaggcactgt
tcctgttgatgaaccctatttcacaggacccctgctaagg
tgatttgaggggaaatgagaggaggctcaaataatcaccc
agcccctgccacttactgaaagtgtaggtccttgtgcccc
acaccatcagagtttctgcgttagcagatttgtggtttgc
ccagcagcctgggcgtgtgcatttctaatgggtgcctcaa
gtgatctgtttctgatttgtatttctattgtgaagagtca
gcccagtactgcaggcctcttacctaagcagaatcccagt
ctggcatcaaagctttagaggacaagttgattcaggcaga
gaagaacttgggctatacaagcgctgttcttcagcattga
agtattttggaggcattagatagtttaaccctttctcagt
caaggaatatttacagaacatgatctctgggcattgtaac
tcctggtcttagtggggaatatagggaccccatgtctcca
tggggtgcacagaatgtctgtgagactgatggagtggaga
acgccatcccccagcctctccagctactcgaggcattctg
tagaacataagcccatagattgtgtgtgtgtgtgtgtgtg
tgtgtgtgtgtgtgtgtgtgtgcatgcgcgcgcgtgcgca
ctggaggaacctaagaaactatttggtgcacttcctctta
ttttagagctcccaaagtgtagctccagaatcgtaaaggg
atatgctcagtctcacagccagcctgtggatctcagtccc
aacactcacccttgtgctactgagtcagctctaagaaaat
ctgccaaaagtaggccgagggctggttttttgttttgttt
tgtttgtttgatacagggtcttcactctgttgcccaggct
ggagtatatcatggctcactgcaaccttgacttgggctca
agcgatccgctcaagtagctggaactactctcaagtagct
ctcaagagcctctcgagtggctggaactacaggcgtgcac
caccacagctggttaatttttaaaattttttgtagagacg
gtggaggaggttctcactgtgactcagtgtgtgcccgaca
gcagagcccacaccactccagttgcagtggttgccatctg
ggtcatcagacctggctgtcaggggtgcagccacaggaga
gccaacagcagagggtgctggccgctgagctagctgctaa
tgctggcctgggtgcagttctcatccaaagtacccggtgg
gtgggagtcactcagtaccagttccgagcctgaacccaaa
ctctcgtgtttctgctcacccctctctggcttctgccacc
acatgggaagaatatgccctggttagcccatggcttctga
agagcaagagaaagtagagcagagcctactccagcctccc
ccgtccaatgtatgaaagccccagctgatctgtaagcctg
ggagcgtgataaatgcttagtagtgcatgccatggagttc
cagggtggtttattacacggcaatatctagctaaatacat
ttaacttgctgcagctctctggatccagcctggttaccag
gaagacaaaaactgggctccaccaggaaccagtcttctgc
cttcccaaccatcacctctggctgcatcagcgatctctcc
cagcgaaatagctgcttggtcttgtgtgaatcctgtactt
taacacagtggaccaagtgtcagtcattgaaaatgaccat
gagtaaccctgtggactctctgcagcttggttcctttgcc
ccttaacaggtgggtatgaatcgtgtcttcagtgccaggg
ctgaatgagaaagggcattcctttttgaaggaatctgata
ctaaacacaaagcatgagaaaaatcaggacttgttggagt
tatatttttaaaatatatattttaacagttatatatatta
gatataatatataatagtatatataaataatactatattg
cccaggctggtctcgaactccttagctcaagtgatcctcc
tgccttggcttcccaaagtgctaggattacaggtgtgagc
cactgctcccggcctgttggagttctttacatttatttta
taatcaatgctgttttattaaatgcggattttattttgga
ttacaggatgtagaatgccatatttttcttagatcatagg
gcctttcacatttgtaatttggccttgtatgagttaccct
gcaatccctttgttttccccataacccttccaaaggaagg
ccgcaatagaaatacaaagagaaacaaaataattagaata
ttttttaacttctaaagttcaaggttttggcataagtctg
gtttagaagcacatttgcctagccctttccttcccaccaa
gggggaaagtcttcctctagacaagaggcagagggctcct
cagagtcagatcctggtgtgggctctcacgtgctgctgct
gaatcccagggaaggagggaggaagggcagttgacaccca
aaataagggtggggaactgtcagcagaggaggtctgtgtc
atgtttttcagcgctggggttggggggagcccaggagagc
aggaagatccagagatccctcgccccagctcggccatgtg
tgtctgggacagagcctgaggtggcctgagcttcctgtgg
ctccagagtaacattatagagaagctgaattctcctgttt
ttctgaaaagggcatgggagttagctgagaagcagacctg
gtgggcctgagagtctcaatcgtcaggtaaggacagtcag
tgggaagtggacgggccgcacaaccaaggttctcatgagg
acaaccatgtcttcgggggtgcccttgtgcacagacagct
ccatagtcctgcctccaatgtcccaacactgcattgtctc
cctgcacttagcagccctgcagggtgagacttggggagga
tcctgaaatgattgtatttaacaagacatgctgtccttgt
ttacctggaacctagcaatgttgttttctgccacaacttg
aatagatacttgaagcagagatgatgttgagttaaaaaaa
atatatacataaaaatatgggttcttttcaacctgaatag
atggcctaaaaattcaaa
MORF4L1 NM_001265603.1 cggcgtgccctggggcggcgcgggcgcaggggcgcgtgcg 14
cggcgggctgtcgttggctggagcagcggctgcgcgggtc
gcggtgctgtgaggtctgcgggcgctggcaaatccggccc
aggatgtagagctggcagtgcctgacggcgcgtctgacgc
ggagttgggtggggtagagagtagggggcggtagtcgggg
gtggtgggagaaggaggaggcggcgaatcacttataaatg
gcgccgaagcaggacccgaagcctaaattccaggaggttg
ggatgaatgggttccggagagcagagtactcaaatacgtg
gacaccaatttgcagaaacagcgagaacttcaaaaagcca
atcaggagcagtatgcagaggggaagatgagaggggctgc
cccaggaaagaagacatctggtctgcaacagaaaaatgtt
gaagtgaaaacgaaaaagaacaaacagaaaacacctggaa
atggagatggtggcagtaccagtgagacccctcagcctcc
tcggaagaaaagggcccgggtagatcctactgttgaaaat
gaggaaacattcatgaacagagttgaagttaaagtaaaga
ttcctgaagagctaaaaccgtggcttgttgatgactggga
cttaattaccaggcaaaaacagctcttttatcttcctgcc
aagaagaatgtggattccattcttgaggattatgcaaatt
acaagaaatctcgtggaaacacagataataaggagtatgc
ggttaatgaagttgtggcagggataaaagaatacttcaac
gtaatgttgggtacccagctactctataaatttgagagac
cacagtatgctgaaattcttgcagatcatcccgatgcacc
catgtcccaggtgtatggagcgccacatctcctgagatta
tttgtacgaattggagcaatgttggcttatacacctctgg
atgagaagagccttgctttattactcaattatcttcacga
tttcctaaagtacctggcaaagaattctgcaactttgttc
agtgccagcgattatgaagtggctcctcctgagtaccatc
ggaaagctgtgtgagaggcactctcactcacttatgtttg
gatctccgtaaacacatttttgttcttagtctatctcttg
tacaaacgatgtgctttgaagatgttagtgtataacaatt
gatgtttgttttctgtttgattttaaacagagaaaaaata
aaagggggtaatagctccttttttcttctttctttttttt
tttcatttcaaaattgctgccagtgttttcaatgatggac
aacagagggatatgctgtagagtgttttattgcctagttg
acaaagctgcttttgaatgctggtggttctattcctttga
cactacgcacttttataatacatgttaatgctatatgaca
aaatgctctgattcctagtgccaaaggttcaattcagtgt
atataactgaacacactcatccatttgtgcttttgttttt
ttttatggtgcttaaagtaaagagcccatcctttgcaagt
catccatgttgttacttaggcattttatcttggctcaaat
tgttgaagaatggtggcttgtttcatggtttttgtatttg
tgtctaatgcacgttttaacatgatagacgcaatgcattg
tgtagctagttttctggaaaagtcaatcttttaggaattg
tttttcagatcttcaataaattttttctttaaatttcaaa
gaacaaaaaaaaaaaaaaa
MRPL19 NM_014763.3 gtagtcttgacgtgagctagctggcatggcggcctgcatt 15
gcagcggggcactgggctgcaatgggcctaggccggagtt
tccaagccgccaggactctgctccccccgccggcctctat
cgcctgcagggtccacgcggggcctgtccggcagcagagc
actgggccttccgagcccggtgcgttccaaccgccgccga
aaccggtcatcgtggacaagcaccgccccgtggaaccgga
acgcaggttcttgagtcctgaattcattcctcgaagggga
agaacagatcctctgaaatttcaaatagaaagaaaagata
tgttagaaaggagaaaagtactccacattccagagttcta
tgttggaagtattcttcgtgttactacagctgacccatat
gccagtggaaaaatcagccagtttctggggatttgcattc
agagatcaggaagaggacttggagctactttcatccttag
gaatgttatcgaaggacaaggtgtcgagatttgctttgaa
ctttataatcctcgggtccaggagattcaggtggtcaaat
tagagaaacggctggatgatagcttgctatacttacgaga
tgcccttcctgaatatagcacttttgatgtgaatatgaag
ccagtagtacaagagcctaaccaaaaagttcctgttaatg
agctgaaagtaaaaatgaagcctaagccctggtctaaacg
ctgggaacgtccaaattttaatattaaaggaatcagattt
gatctttgtttaactgaacagcaaatgaaagaagctcaga
agtggaatcagccatggcttgaatttgatatgatgaggga
atatgatacttcaaaaattgaagctgcaatatggaaggaa
attgaagcgtcgaaaaggtcttgattctgagaatgaattt
ggttagttgcagaagatacattggctctaagaggatatat
tttgagaccaatttaatttcatttataagaacatagtaat
taagtgaactaagcattcattgttttattaatactttttt
tctaaaataaaacttgtacaccagtttattactctaaaaa
gagaattacacatgccaaatggaccaatgtccatttgctt
attggaggcaaagctacaatagaagtcagagcatcaccag
aatggtctttaatgagcatggaacctgagcaaagggaata
ggtgggatgaattttttttttaattgtgaaacaattcata
agcacaatatgatttacagaataataaacattcatgtacc
cactatcaggttaagaaatagaacatttattaatatgtag
gaatgttaagaaataaaacatttaataagatctcagaaga
ctccagtaaatctgcaattgtatctctctcctttttaaat
gtaaatatcatcttgacttgttaattattcccttgcattt
cttttagtttactgccaacacatatattcttcaacaatat
atttaattttgaaaaacctgaaaaaaaaaacctgttagca
agtataaaggggcagtattactattattgcatgaaggctt
caagggaaacgttacagtctttgggtcatagtctggcttc
agcttcctctgagagtttacagaggccaattttgagcaaa
ttcatggctaaggttatgagtgagttctgctaaacagaag
gctcaccacaaggtatctggcaggattatactgggtagct
ggatgttgcagaaatgtggttagaggaagtaaactgtttt
ttgatgctcacagcatgatgaatcaaactctgtatcttag
gattaggttaaaacaatacctttggtatgatatgagtgtt
gttgctgatccatgcagcatggattggaaagctggggtat
aagcacacatgctaaagaaaaacatgtaatttggtccata
ctcacctggatatactgttcctcaggttaaaaaatacagt
actatcctaaatcttgaaggcaactctcagcctatccatt
gagttaccttcagatctgccctctggttcctagctgtctt
gggactaacttctttcctgcgctcagctgttttctggatt
ccatgttttccattttattgagtactaacttgttttgctg
cagcacatcctttggtagcttctagaggaagtttgtgtgg
aggtaaaatttttgagaccttgcatgtctcatgtttgatt
gatactttatacgtttaggtaggaggtaattttccttcag
gactttaaaaatattgttgctccattttctttgtttctat
tgttgtattgagaaatccaatgccattttgatttccccat
cataaatttcatgatgatgtgtcttggtgtgggtctatat
ttatccattgtattgggttttaggtgaacccttccagata
gtaactcatttctgtcagttctgggaaacacttagcattg
gttgatgatttattctctgctgctttgttctcccaactat
tatttggatgttggatatccagcactgggtatctattttc
ttacctccctcccttgaccccagtctctgttttttagctc
tttagctcaatcttccaactctttgctattgtattttaaa
atcttaagaccccttcttgatttgtagaagttccttttct
tacaaccaaaaagcctttatctatggatttgttcacagat
aaggggtattcaatatagtgtatttttttttcatttaaaa
ttgtttgcgcatctatttcctccaaatttctttctgtatt
tattttttgttgtctatatttcagacttttccaggatatc
tgataatctttggctgtcttcttatggttgaaagagggac
taaaaagcttggaaagcctttgggttgtgggaaggggctg
tctttaggattatctgaatgggcttttttgggagtcccct
cctccacatgaatattttggttttgtcagattccctagaa
tagaggcttccaatctccttcctggaggggtctgtccagg
aaggagattgtctaggggtctgtcagacagcagctttcag
ctacttccttgatctttttcactaatgattatatagtcat
ctaactactgtcaacaagtaatagatatcctatccttcac
ttgtttagattatttgctgagataacctctcaaaagaacc
tctcaaaataaaaggttaacaagagcctatatcttatatt
tttcttctctttatcttgttagaagatagctattaaaacc
tgttctttttctgtcttgataaacacacttcaatcttggt
agaatggtagatgggacagtatattttaggacctaaagct
ctgcaaatgtatgatcagcttgtaagtacaggtgctcaaa
aacatgtaaacaatcatgctttttactctgtaggaatatc
tttaaaattcttgtgaatttttccccagaagtaaagcaaa
tcttcccccagaaataaaattaaatgtgcataatctaaag
ctttttttttttattgtggtaggatatatatataaaacat
aatttgccattgtaaacattttaaatttacaagtcagagg
cattaattacatcacaatgttgtgaaattattactactat
ttccaaaattttctcatcaccccaaactgaaactctgtaa
ctgttgagcaataacctcattcctgtatctctcccaaccc
caggtaacctcaaatctttctttttatctttgagacaagg
tctcattctatcactcaggtaggagtgcagtggtgtgatc
atagctcattgcagcctcaaaatcctgggctcaagcaatc
ctccttgagtagctaagactataggcacacattaactgcg
cctggctgattttgttttttgtagagatgtggtcttgcta
tgtttcccatgctggtcttgagttcctggcctcaagcagt
ccttaagattcatccatgttgtggcatgtgtcagaatttc
atttgtttttatgactaaataatattccattgtatgtata
tacattttgttcatccatcttctgatgaacactgggatat
gtctaccttttggctattgtgaataatgctgcagtaaaca
ttgacataacaagtatgtatttgattgcctgtttctaagt
tcttttgggtatacatcttgagtagaattgctagataatg
tcatgttttatttctcttgtgatttcttcttcgatcccct
ggttgagtgtgttaatttctacatgtttatgaatttccca
ctgtttttttgttattgatttccaagttcattccattgtg
attagagaagatacttagtatgattttaatgtttttgaga
attggtgtgtggcctgatagatggtctgtcctggagaatg
ttcctcatacacttgagcaaaatatttatcatgctattgt
tgactgtagttttctatatgtctcttaggtcaaggtggtt
tacaatgtgttaaggttctctttttttaaaaaaatttttg
cacagagtatctttttctatgtgttccatgtatttgtgtc
tttggagctatagtctcttgtagacagcatatcactatct
tgttttgttttgttttttctgtccattctgccaatttctg
ccttttgattggaaaatttaatccatttgcatttaaagta
attaaggaaggactttcttctaccatttaacacttcttct
atatgtcatatacttttttggcccctcatttcctctttat
ggccttcttttctgtttttttgtagtgaactagtctgatt
ctctttccactcccctttgtgtatatttgttagatgtttt
atttgtggttgctatggggattatagttaacatcctacac
ttaaaacaatctaatttaaactgataccaatttaccttca
atagcatacaaaatctctactcctgtaaagctctgcccct
gccccccttatgttattgatggcacaaattgcctaataaa
taatttatagttatttgtatgagtttgtcttttaaatcat
ttaggaaataaaaagtggagttagaaaacagtatgatagt
aatactgacttttatatttgtcaatatatttatcttattt
tggatccttatttcattatatagatttgagttactgtcta
gtgcccttccatttcggcccaaaggattcccttatgcatt
tcttgcagggcaagtctaattgtaataaactccctcagct
tttgttttatctgagaatgtcttgatttctcccttatttt
tgatggataattttgccagatacatgaatttttggtaaca
gtatttttctttcagcactttaaatatgtcatcccactac
cttctgacttcatggtttctcatgagatattagatgttat
aaaatttgaggattcctcattcttgatgagtcagttctgt
cttattgcttttcggatttgctcagcttttgtcttttgac
agtttgattataacgcggctcagtgtgggtctctgagttt
atcccacttagagtttgttgagtttcttggagtcatagat
ttatgtcttttatcaaattttggacatatttggctattat
ttcttcaatttttttcactgcttctttcttttccttctga
aatattcttaatgtatatgttggtctgtttgatgctgtct
caccagtttcttaggctgtgttctcttttgttcctcagac
ttgattattgcagttgcccttctttttatttttttcaagt
ttgttgattcttctccctgttcagatcaactgttgaactc
ctctagtgaatttatttcagttactgtacttttcagctcc
aagatttatctttggttcctttttataacgtctgtgtctt
tattgatattctcattttgttcatatgtctctttcttcct
ttagttctttgtccatgttttcctttagctctttgggctt
atttaagacaattgtttaaagtctttgcatagtaagtcca
atgtctgtgtttcttcagggatggttttcattattttgtt
ttcaatgagccatactttcctgtgtctttgtatgctgtct
ttttgttgttgaaaactgtatgtttgaacatcataacgtg
gtggccctgaaaatcagatattccccccttcctgagagtt
agttttatttttattattgaagattgtagcagtctattgc
tacatgtgcagtcatttccaaactatttttgcaaagactg
tattccttctgtgtgtcatcactgaagtctctgttcctta
gtttgtgtttaatagtttgacatagatttccttgaaagga
gttaaaactagcagaaaaatctctctcccagtctttccag
tctttgtagattggttctgtgctgggcttttccattaata
cttagccaggcttgtactgagcctaacaatcaggcccaaa
agcgtagggtctttgcagatcttgtctgagcatgcttctt
gctgtgtatgcacgtagttttctaaatctccctgtatgtg
ctgttgaatattctaatttcccaaagaaactcctttgcag
ctttttctcacagaacatagatggttttttggatatcttg
accatagtctttcgacccaggtgtttgcggttgttagttc
accttacacttttttcaagcattgcctactgcttacgatg
agtgctctgtcaatcctttaagtagccccagacaggctac
cagagacttaaacaagaatttgtaagttctgctcagcttc
ctctagaaatggggatcagggtccaagacagaatgcagtt
gctgatttcaagactgctgcaacaccagggagcttgtggg
ggaagggcaagcagaaatgtcacaaagctttcttgccatt
ttaaagttgcctgttcttgactcagcatttgcttcattgc
tataaactttttactgtttttcagagttctgataaaattg
gctatgcctgttcctgctttaaaaaatatatatatatttt
ttagggattggggtctcactatactgaccaggctggtctt
gaacttctggcctcaagccatcctctcatttcagcttccc
aaagtgctgcaattacacgcgtgaaccaccacacccagcc
cctgcttgtttttcaatgtgcctactccaccatgttgctc
aagtatgtatattttctaaactaccttgtagtgttgtgat
gggaaataaatccctgagccttttgaataactcagagaga
tcaaaaacttagtttatcctattcgaaggattagaaaaat
gatatatctttcactttttcagggataggctcctcattag
aaggctcctatgtgccgatgctgtacaagacatttcattt
ctcttaatgtttacaacaagcttgttgccaaggctgatct
tgaactcctggcctcaaacgatcctcccagctcagtctca
caaagtgttgggatgtctggccaactaatgactatcttaa
ctcttgtgtttcaatgtttatgccttcttttatcttgact
gattgtatgactatgtcttctagaacaatgttgaacagaa
atggtgagagcagacatccttgctttaatatttcaccatt
atatatgatgttaggtatagatttttctcacagatgcctt
ttatcagattgaggaatttatattcctactttgccgaaag
gtttttgtagtatgagggggtgctgaattttgtcaaacac
tttttcggtaataattgagatgattggttctgcagtcatc
gagatgtggattttctcctttattctgttcgtgagtgatt
acactggttgactaatgttaaaacaaccttactttccagg
aataaaccctattatcttttttataca
PSMC4 NM_153001.2 tgcgggtacggacagcgcatgagcttatgttgagggcgga 16
gcccagaccagcccttcgtcctatcctgcccttccagcac
ctctcagccgtaacttaaactacacttcccagaagcctcc
tcagccagggacttccgttgtcgtcagcggaagcggtgac
agatcatcccaggccacacagaggccggcttggtcactat
ggaggagataggcatcttggtggagaaggctcaggatgag
atcccagcactgtccgtgtcccggccccagaccggcctgt
ccttcctgggccctgagcctgaggacctggaggacctgta
cagccgctacaaggaggaggtgaagcgaatccaaagcatc
ccgctggtcatcggacaatttctggaggctgtggatcaga
atacagccatcgtgggctctaccacaggctccaactatta
tgtgcgcatcctgagcaccatcgatcgggagctgctcaag
cccaacgcctcagtggccctccacaagcacagcaatgcac
tggtggacgtgctgccccccgaagccgacagcagcatcat
gatgctcacctcagaccagaagccagatgtgatgtacgcg
gacatcggaggcatggacatccagaagcaggaggtgcggg
aggccgtggagctcccgctcacgcatttcgagctctacaa
gcagatcggcatcgatcccccccgaggcgtcctcatgtat
ggcccacctggctgtgggaagaccatgttggcaaaggcgg
tggcacatcacacaacagctgcattcatccgggtcgtggg
ctcggagtttgtacagaagtatctgggtgagggcccccgc
atggtccgggatgtgttccgcctggccaaggagaatgcac
ctgccatcatcttcatagacgagattgatgccatcgccac
caagagattcgatgctcagacaggggccgacagggaggtt
cagaggatcctgctggagctgctgaatcagatggatggat
ttgatcagaatgtcaatgtcaaggtaatcatggccacaaa
cagagcagacaccctggatccggccctgctacggccagga
cggctggaccgtaaaattgaatttccacttcctgaccgcc
gccagaagagattgattttctccactatcactagcaagat
gaacctctctgaggaggttgacttggaagactatgtggcc
cggccagataagatttcaggagctgatattaactccatct
gtcaggagagtggaatgttggctgtccgtgaaaaccgcta
cattgtcctggccaaggacttcgagaaagcatacaagact
gtcatcaagaaggacgagcaggagcatgagttttacaagt
gacccttcccttccctccaccacaccactcaggggctggg
gcttctctcgcacccccagcacctctgtcccaaaacctca
ttcccttttttctttacccaggattggtttcttcaataaa
tagataagatcgaatccatttaatttcttcttagaagttt
aactcctttggagaatgtgggccttgaataggatcctctg
ggtccctcttaatctgacagatgagcagacgaggtgcatg
gcctgggttgcagcttgagagaaccaaaatattcaaacca
gatgacttccaaaatgtggggaaagggatggaaaatgaac
ctgagatggagtccttaatcacgggataaagccctgtgca
tctccctcatttcctacaggtaaaagacagtaaagaaatt
caggtcacaggccttgggagttcataggaaggagatgtcc
agtgctgtccagtagaacttt
SF3A1 NM_005877.5 ggtcccggaagtgcgccagtcgtaccttcgcggccgcaac 17
tcgctcggccgccgccatcttgcgagctcgtcgtactgac
cgagcggggaggctgtcttgaggcggcaccgctcaccgac
accgaggcggactggcagccctgagcgtcgcagtcatgcc
ggccggacccgtgcaggcggtgcccccgccgccgcccgtg
cccacggagcccaaacagcccacagaagaagaagcatctt
caaaggaggattctgcaccttctaagccagttgtggggat
tatttaccctcctccagaggtcagaaatattgttgacaag
actgccagctttgtggccagaaacgggcctgaatttgaag
ctaggatccgacagaacgagatcaacaaccccaagttcaa
ctttctgaaccccaatgacccttaccatgcctactaccgc
cacaaggtcagcgagttcaaggaagggaaggctcaggagc
cgtccgccgccatccccaaggtcatgcagcagcagcagca
gaccacccagcagcagctgccccagaaggtccaagcccaa
gtaatccaagagaccatcgtgcccaaagagcctcctcctg
agtttgagttcattgctgatcctccctctatctcagcctt
cgacttggatgtggtgaagctgacggctcagtttgtggcc
aggaatgggcgccagtttctgacccagctgatgcagaaag
agcagcgcaactaccagtttgactttctccgcccacagca
cagcctcttcaactacttcacgaagctagtggaacagtac
accaagatcttgattccacccaaaggtttattttcaaagc
tcaagaaagaggctgaaaacccccgagaagttttggatca
ggtgtgttaccgagtggaatgggccaaattccaggaacgt
gagaggaagaaggaagaagaggagaaggagaaggagcggg
tggcctatgctcagatcgactggcatgattttgtggtggt
ggaaacagtggacttccaacccaatgagcaagggaacttc
cctccccccaccacgccagaggagctgggggcccgaatcc
tcattcaggagcgctatgaaaagtttggggagagtgagga
agttgagatggaggtcgagtctgatgaggaggatgacaaa
caggagaaggcggaggagcctccttcccagctggaccagg
acacccaagtacaagatatggatgagggttcagatgatga
agaagaagggcagaaagtgcccccacccccagagacaccc
atgcctccacctctgcccccaactccagaccaagtcattg
tccgcaaggattatgatcccaaagcctccaagcccttgcc
tccagcccctgctccagatgagtatcttgtgtcccccatt
actggggagaagatccccgccagcaaaatgcaggaacaca
tgcgcattggacttcttgaccctcgctggctggagcagcg
ggatcgctccatccgtgagaagcagagcgatgatgaggtg
tacgcaccaggtctggatattgagagcagcttgaagcagt
tggctgagcggcgtactgacatcttcggtgtagaggaaac
agccattggtaagaagatcggtgaggaggagatccagaag
ccagaggaaaaggtgacctgggatggccactcaggcagca
tggcccggacccagcaggctgcccaggccaacatcaccct
ccaggagcagattgaggccattcacaaggccaaaggcctg
gtgccagaggatgacactaaagagaagattggccccagca
agcccaatgaaatccctcaacagccaccgccaccatcttc
agccaccaacatccccagctcggctccacccatcacttca
gtgccccgaccacccacaatgccacctccagttcgtacta
cagttgtctccgcagtacccgtcatgccccggcccccaat
ggcatctgtggtccggctgcccccaggctcagtgatcgcc
cccatgccgcccatcatccacgcgcccagaatcaacgtgg
tgcccatgcctccctcggcccctcctattatggccccccg
cccaccccccatgattgtgccaacagcctttgtgcctgct
ccacctgtggcacctgtcccagctccagccccaatgcccc
ctgtgcatcccccacctcccatggaagatgagcccacctc
caaaaaactgaagacagaggacagcctcatgccagaggag
gagttcctgcgcagaaacaagggtccagtgtccatcaaag
tccaggtgcccaacatgcaggataagacggaatggaaact
gaatgggcaggtgctggtcttcacccteccactcacggac
caggtctctgtcattaaggtgaagattcatgaagccacag
gcatgcctgcagggaaacagaagctacagtatgagggtat
cttcatcaaagattccaactcactggcttactacaacatg
gccaatggcgcagtcatccacctggccctcaaggagagag
gcgggaggaagaagtagacaagaggaacctgctgtcaagt
ccctgccattttgcctctcctgtctcccaccccctgcccc
agacccaggagcccccctgaggctttgccttgcctgcata
tttgtttcgctcttactcagtttgggaattcaaattgtcc
tgcagaggttcattcccctgaccctttccccacattggta
agagtagctgggttttctaagccactctctggaatctctt
tgtgttagggtctcgatttgaggacattcatttcttcagc
agcccattagcaactgagagcccagggatgtcctacagga
tagtttcatagtgacaggtggcacttggctaatagaatat
ggctgatattgtcattaatcattttgtaccttgacatggg
ttgtctaataaaactcggacccttcttgtgaaatcagtta
aataagacttgtctcggtcacctgtgccctgtccagactc
gaggcagtggtaacactgcacagtgctatgtggcttctct
ttgaggatttttgggttttgtaactaaattcttgctgccc
tcatactttttatgtattagaatcatattcgtattgccct
tttaaaacattgggatcctccaaaggcctgccccatgtat
ttaacagtaatacaggaagcatggcaggcaccatgcaaac
caaggatggatggtgcagtccctgtgtcagtgggcggtgg
tttcctgctggcctggaatcactcatcacctgattgattg
gctctgtggtcctgggcaggtgcctcataggtgtgtggat
atgatgacgtttctttaaaatgtatgtatttaacaaatac
ttaattgtattaaggtcatgtaccaaggatttgataaagt
ttaaataatttactctctacttttatccattttatccatt
ttaactcatgtaatcctcatgtgagtattcctgtttaaca
cttgagtaaactgaggcacagagaacataagttgcatgcc
atagtcacacactgtgaaagtgaaaagagaatgtgtgcaa
aacacgtcacagtcctggtttctgagtaaaggcaggctgt
tatctttagaatcaagctatcacagggagataggcaatgc
tgtgggtgttggaggaaggtgagagcctgttgctaacaat
ttcctggttttaaagctaaggctgattttattgggaagat
ctcacatgtgtgtggcccctgagagttcccagtgcctttt
atttgcagtccttccatttggacctcctagctgccccatc
aggtcatctccagggctcagaggggtgagaccatttccca
aggtcacagaaccagctctctagtcaccaccctgcctctc
cctctcacccagagtcagtaccagttttatggctttatta
caaactgctgggtccctcccattttcaacttgattgatgg
gatgtcatcccttatcctgtctgacatttgcctctggcct
ggttgctagaagtttgccccaggggcaagagttgaaattt
ggcttcctgaggtgggctttgtggtttgcgtccctaaagt
gagcccactactggttgcttgtccatggccaacaccagaa
atcccctgagcactacctgggtctcattccaagaaggaag
agggtcaggagacctggggagtctcatattccaagttctt
ctttctttctgggagcagtgggcagttcatggtgttaggg
cactcacccccacagactggcaaaccctgcaggacttccg
tggctgaggctgtgaccggaggccaggaatgccgttgggt
ggattgtgagtgaatgggccctttgagctgccctctagag
agcaaatccagtttcctggagctcctgaatgaatatctgt
actggctcgctcagatgcagaagctccattgaccatgagg
ccttgtgaacatcagtggccacaggcccagtgtgctgctt
ggcactgcactagtttaggacctgcagcatgtaggtagcg
tcctagtgtttataatacaaagctgctctgcacagctttt
ctgattcttcttgcaatctcctgaggattatctgccccat
ttttaaaacgaggtggaatacccaaggtcatgtagccagt
gagtgctctggaaagccaaagcagctcatcccttcctggg
gaccacactgctctgctccaccagaccacactatgaaata
ggaataagtgctcctgttgcaggactgctgggaaaacagg
tggtgtgggacttaagtcaccataattttgaagacttgca
tgcagagggctccaggaattgtagacattaaggaatttca
ctttcagttctacccactacttaagtacttgtcatgtact
cttagaggaggccagtaatgatcagaaccattttacttta
aaattaataatattgtattagagaatatattaaatggtta
tattgggttatgttaggatatatacttgaatggaaataca
tgtactattagcaatcatatttcatttatccctgtaatta
gacaagaaagcataatatagctctactcatgggtacacat
accagtgtataagatttttagaagtttactttttaaaaat
aaaagcaaaatgtaagatcttaaaaaaaaaaaaaaaaaa
PUM1 NM_001020658.1 agtgggccgccatgttgtcggagtgaaaggtaagggggag 18
cgagagcgccagagagagaagatcggggggctgaaatcca
tcttcatcctaccgctccgcccgtgttggtggaatgagcg
ttgcatgtgtcttgaagagaaaagcagtgctttggcagga
ctctttcagcccccacctgaaacatcaccctcaagaacca
gctaatcccaacatgcctgttgttttgacatctggaacag
ggtcgcaagcgcagccacaaccagctgcaaatcaggctct
tgcagctgggactcactccagccctgtcccaggatctata
ggagttgcaggccgttcccaggacgacgctatggtggact
acttctttcagaggcagcatggtgagcagcttgggggagg
aggaagtggaggaggcggctataataatagcaaacatcga
tggcctactggggataacattcatgcagaacatcaggtgc
gttccatggatgaactgaatcatgattttcaagcacttgc
tctggagggaagagcgatgggagagcagctcttgccaggt
aaaaagttttgggaaacagatgaatccagcaaagatggac
caaaaggaatattcctgggtgatcaatggcgagacagtgc
ctggggaacatcagatcattcagtttcccagccaatcatg
gtgcagagaagacctggtcagagtttccatgtgaacagtg
aggtcaattctgtactgtccccacgatcggagagtggggg
actaggcgttagcatggtggagtatgtgttgagctcatcc
ccgggcgattcctgtctaagaaaaggaggatttggcccaa
gggatgcagacagtgatgaaaacgacaaaggtgaaaagaa
gaacaagggtacgtttgatggagataagctaggagatttg
aaggaggagggtgatgtgatggacaagaccaatggtttac
cagtgcagaatgggattgatgcagacgtcaaagattttag
ccgtacccctggtaattgccagaactctgctaatgaagtg
gatcttctgggtccaaaccagaatggttctgagggcttag
cccagctgaccagcaccaatggtgccaagcctgtggagga
tttctccaacatggagtcccagagtgtccccttggacccc
atggaacatgtgggcatggagcctcttcagtttgattatt
caggcacgcaggtacctgtggactcagcagcagcaactgt
gggactttttgactacaattctcaacaacagctgttccaa
agacctaatgcgcttgctgtccagcagttgacagctgctc
agcagcagcagtatgcactggcagctgctcatcagccgca
catcggtttagctcccgctgcgtttgtccccaatccatac
atcatcagcgctgctcccccagggacggacccctacacag
ctggattggctgcagcagcgacactaggcccagctgtggt
ccctcaccagtattatggagttactccctggggagtctac
cctgccagtcttttccagcagcaagctgccgctgccgctg
cagcaactaattcagctaatcaacagaccaccccacaggc
tcagcaaggacagcagcaggttctccgtggaggagccagc
caacgtcctttgaccccaaaccagaaccagcagggacagc
aaacggatccccttgtggcagctgcagcagtgaattctgc
ccttgcatttggacaaggtctggcagcaggcatgccaggt
tatccggtgttggctcctgctgcttactatgaccaaactg
gtgcccttgtagtgaatgcaggcgcgagaaatggtcttgg
agctcctgttcgacttgtagctcctgccccagtcatcatt
agttcctcagctgcacaagcagctgttgcagcagccgcag
cttcagcaaatggagcagctggtggtcttgctggaacaac
aaatggaccatttcgccctttaggaacacagcagcctcag
ccccagccccagcagcagcccaataacaacctggcatcca
gttctttctacggcaacaactctctgaacagcaattcaca
gagcagctccctcttctcccagggctctgcccagcctgcc
aacacatccttgggattcggaagtagcagttctctcggcg
ccaccctgggatccgcccttggagggtttggaacagcagt
tgcaaactccaacactggcagtggctcccgccgtgactcc
ctgactggcagcagtgacctttataagaggacatcgagca
gcttgacccccattggacacagtttttataacggccttag
cttttcctcctctcctggacccgtgggcatgcctctccct
agtcagggaccaggacattcacagacaccacctccttccc
tctcttcacatggatcctcttcaagcttaaacctgggagg
actcacgaatggcagtggaagatacatctctgctgctcca
ggcgctgaagccaagtaccgcagtgcaagcagcgcctcca
gcctcttcagcccgagcagcactcttttctcttcctctcg
tttgcgatatggaatgtctgatgtcatgccttctggcagg
agcaggcttttggaagattttcgaaacaaccggtacccca
atttacaactgcgggagattgctggacatataatggaatt
ttcccaagaccagcatgggtccagattcattcagctgaaa
ctggagcgtgccacaccagctgagcgccagcttgtcttca
atgaaatcctccaggctgcctaccaactcatggtggatgt
gtttggtaattacgtcattcagaagttctttgaatttggc
agtcttgaacagaagctggctttggcagaacggattcgag
gccacgtcctgtcattggcactacagatgtatggctgccg
tgttatccagaaagctcttgagtttattccttcagaccag
caggtaattaatgagatggttcgggaactagatggccatg
tcttgaagtgtgtgaaagatcagaatggcaatcacgtggt
tcagaaatgcattgaatgtgtacagccccagtctttgcaa
tttatcatcgatgcgtttaagggacaggtatttgccttat
ccacacatccttatggctgccgagtgattcagagaatcct
ggagcactgtctccctgaccagacactccctattttagag
gagcttcaccagcacacagagcagcttgtacaggatcaat
atggaaattatgtaatccaacatgtactggagcacggtcg
tcctgaggataaaagcaaaattgtagcagaaatccgaggc
aatgtacttgtattgagtcagcacaaatttgcaagcaatg
ttgtggagaagtgtgttactcacgcctcacgtacggagcg
cgctgtgctcatcgatgaggtgtgcaccatgaacgacggt
ccccacagtgccttatacaccatgatgaaggaccagtatg
ccaactacgtggtccagaagatgattgacgtggcggagcc
aggccagcggaagatcgtcatgcataagatccggccccac
atcgcaactcttcgtaagtacacctatggcaagcacattc
tggccaagctggagaagtactacatgaagaacggtgttga
cttagggcccatctgtggcccccctaatggtatcatctga
ggcagtgtcacccgctgttccctcattcccgctgacctca
ctggcccactggcaaatccaaccagcaaccagaaatgttc
tagtgtagagtctgagacgggcaagtggttgctccaggat
tactccctcctccaaaaaaggaatcaaatccacgagtgga
aaagcctttgtaaatttaattttattacacataacatgta
ctattttttttaattgactaattgccctgctgttttactg
gtgtataggatacttgtacataggtaaccaatgtacatgg
gaggccacatattttgttcactgttgtatctatatttcac
atgtggaaactttcagggtggttggtttaacaaaaaaaaa
aagctttaaaaaaaaaagaaaaaaaggaaaaggtttttag
ctcatttgcctggccggcaagttttgcaaatagctcttcc
ccacctcctcattttagtaaaaaacaaacaaaaacaaaaa
aacctgagaagtttgaattgtagttaaatgaccccaaact
ggcatttaacactgtttataaaaaatatatatatatatat
atatatatataatgaaaaaggtttcagagttgctaaagct
tcagtttgtgacattaagtttatgaaattctaaaaaatgc
cttttttggagactatattatgctgaagaaggctgttcgt
gaggaggagatgcgagcacccagaacgtcttttgaggctg
ggcgggtgtgattgtttactgcctactggatttttttcta
ttaacattgaaaggtaaaatctgattatttagcatgagaa
aaaaaaatccaactctgcttttggtcttgcttctataaat
atatagtgtatacttggtgtagactttgcatatatacaaa
tttgtagtattttcttgttttgatgtctaatctgtatcta
taatgtaccctagtagtcgaacatacttttgattgtacaa
ttgtacatttgtatacctgtaatgtaaatgtggagaagtt
tgaatcaacataaacacgttttttggtaagaaaagagaat
tagccagccctgtgcattcagtgtatattctcacctttta
tggtcgtagcatatagtgttgtatattgtaaattgtaatt
tcaaccagaagtaaatttttttcttttgaaggaataaatg
ttctttatacagcctagttaatgtttaaaaagaaaaaaat
agcttggttttatttgtcatctagtctcaagtatagcgag
attctttctaaatgttattcaagattgagttctcactagt
gtttttttaatcctaaaaaagtaatgttttgattttgtga
cagtcaaaaggacgtgcaaaagtctagccttgcccgagct
ttccttacaatcagagcccctctcaccttgtaaagtgtga
atcgcccttcccttttgtacagaagatgaactgtattttg
cattttgtctacttgtaagtgaatgtaacatactgtcaat
tttccttgtttgaatatagaattgtaacactacacggtgt
acatttccagagccttgtgtatatttccaatgaacttttt
tgcaagcacacttgtaaccatatgtgtataattaacaaac
ctgtgtatgcttatgcctgggcaactattttttgtaactc
ttgtgtagattgtctctaaacaatgtgtgatctttatttt
gaaaaatacagaactttggaatctgaaaaaaaaaaaaaaa
aaaaaaaaaaaaaaaa
ACTB NM_001101.4 gagtgagcggcgcggggccaatcagcgtgcgccgttccga 19
aagttgccttttatggctcgagcggccgcggcggcgccct
ataaaacccagcggcgcgacgcgccaccaccgccgagacc
gcgtccgccccgcgagcacagagcctcgcctttgccgatc
cgccgcccgtccacacccgccgccagctcaccatggatga
tgatatcgccgcgctcgtcgtcgacaacggctccggcatg
tgcaaggccggcttcgcgggcgacgatgccccccgggccg
tcttcccctccatcgtggggcgccccaggcaccagggcgt
gatggtgggcatgggtcagaaggattcctatgtgggcgac
gaggcccagagcaagagaggcatcctcaccctgaagtacc
ccatcgagcacggcatcgtcaccaactgggacgacatgga
gaaaatctggcaccacaccttctacaatgagctgcgtgtg
gctcccgaggagcaccccgtgctgctgaccgaggcccccc
tgaaccccaaggccaaccgcgagaagatgacccagatcat
gtttgagaccttcaacaccccagccatgtacgttgctatc
caggctgtgctatccctgtacgcctctggccgtaccactg
gcatcgtgatggactccggtgacggggtcacccacactgt
gcccatctacgaggggtatgccctcccccatgccatcctg
cgtctggacctggctggccgggacctgactgactacctca
tgaagatcctcaccgagcgcggctacagcttcaccaccac
ggccgagcgggaaatcgtgcgtgacattaaggagaagctg
tgctacgtcgccctggacttcgagcaagagatggccacgg
ctgcttccagctcctccctggagaagagctacgagctgcc
tgacggccaggtcatcaccattggcaatgagcggttccgc
tgccctgaggcactcttccagccttccttcctgggcatgg
agtcctgtggcatccacgaaactaccttcaactccatcat
gaagtgtgacgtggacatccgcaaagacctgtacgccaac
acagtgctgtctggcggcaccaccatgtaccctggcattg
ccgacaggatgcagaaggagatcactgccctggcacccag
cacaatgaagatcaagatcattgctcctcctgagcgcaag
tactccgtgtggatcggcggctccatcctggcctcgctgt
ccaccttccagcagatgtggatcagcaagcaggagtatga
cgagtccggcccctccatcgtccaccgcaaatgcttctag
gcggactatgacttagttgcgttacaccctttcttgacaa
aacctaacttgcgcagaaaacaagatgagattggcatggc
tttatttgttttttttgttttgttttggtttttttttttt
ttttggcttgactcaggatttaaaaactggaacggtgaag
gtgacagcagtcggttggagcgagcatcccccaaagttca
caatgtggccgaggactttgattgcacattgttgtttttt
taatagtcattccaaatatgagatgcgttgttacaggaag
tcccttgccatcctaaaagccaccccacttctctctaagg
agaatggcccagtcctctcccaagtccacacaggggaggt
gatagcattgctttcgtgtaaattatgtaatgcaaaattt
ttttaatcttcgccttaatacttttttattttgttttatt
ttgaatgatgagccttcgtgcccccccttccccctttttt
gtcccccaacttgagatgtatgaaggcttttggtctccct
gggagtgggtggaggcagccagggcttacctgtacactga
cttgagaccagttgaataaaagtgcacaccttaaaaatga
ggaaaaaaaaaaaaaaaaaa
GAPD NM_002046.6 gctctctgctcctcctgttcgacagtcagccgcatcttct 20
tttgcgtcgccagccgagccacatcgctcagacaccatgg
ggaaggtgaaggtcggagtcaacggatttggtcgtattgg
gcgcctggtcaccagggctgcttttaactctggtaaagtg
gatattgttgccatcaatgaccccttcattgacctcaact
acatggtttacatgttccaatatgattccacccatggcaa
attccatggcaccgtcaaggctgagaacgggaagcttgtc
atcaatggaaatcccatcaccatcttccaggagcgagatc
cctccaaaatcaagtggggcgatgctggcgctgagtacgt
cgtggagtccactggcgtcttcaccaccatggagaaggct
ggggctcatttgcaggggggagccaaaagggtcatcatct
ctgccccctctgctgatgcccccatgttcgtcatgggtgt
gaaccatgagaagtatgacaacagcctcaagatcatcagc
aatgcctcctgcaccaccaactgcttagcacccctggcca
aggtcatccatgacaactttggtatcgtggaaggactcat
gaccacagtccatgccatcactgccacccagaagactgtg
gatggcccctccgggaaactgtggcgtgatggccgcgggg
ctctccagaacatcatccctgcctctactggcgctgccaa
ggctgtgggcaaggtcatccctgagctgaacgggaagctc
actggcatggccttccgtgtccccactgccaacgtgtcag
tggtggacctgacctgccgtctagaaaaacctgccaaata
tgatgacatcaagaaggtggtgaagcaggcgtcggagggc
cccctcaagggcatcctgggctacactgagcaccaggtgg
tctcctctgacttcaacagcgacacccactcctccacctt
tgacgctggggctggcattgccctcaacgaccactttgtc
aagctcatttcctggtatgacaacgaatttggctacagca
acagggtggtggacctcatggcccacatggcctccaagga
gtaagacccctggaccaccagccccagcaagagcacaaga
ggaagagagagaccctcactgctggggagtccctgccaca
ctcagtcccccaccacactgaatctcccctcctcacagtt
gccatgtagaccccttgaagaggggaggggcctagggagc
cgcaccttgtcatgtaccatcaataaagtaccctgtgctc
aaccagttaaaaaaaaaaaaaaaaaaaaa
GUSB NM_000181.3 gtcctcaaccaagatggcgcggatggcttcaggcgcatca 21
cgacaccggcgcgtcacgcgacccgccctacgggcacctc
ccgcgcttttcttagcgccgcagacggtggccgagcgggg
gaccgggaagcatggcccgggggtcggcggttgcctgggc
ggcgctcgggccgttgttgtggggctgcgcgctggggctg
cagggcgggatgctgtacccccaggagagcccgtcgcggg
agtgcaaggagctggacggcctctggagcttccgcgccga
cttctctgacaaccgacgccggggcttcgaggagcagtgg
taccggcggccgctgtgggagtcaggccccaccgtggaca
tgccagttccctccagcttcaatgacatcagccaggactg
gcgtctgcggcattttgtcggctgggtgtggtacgaacgg
gaggtgatcctgccggagcgatggacccaggacctgcgca
caagagtggtgctgaggattggcagtgcccattcctatgc
catcgtgtgggtgaatggggtcgacacgctagagcatgag
gggggctacctccccttcgaggccgacatcagcaacctgg
tccaggtggggcccctgccctcccggctccgaatcactat
cgccatcaacaacacactcacccccaccaccctgccacca
gggaccatccaatacctgactgacacctccaagtatccca
agggttactttgtccagaacacatattttgactttttcaa
ctacgctggactgcagcggtctgtacttctgtacacgaca
cccaccacctacatcgatgacatcaccgtcaccaccagcg
tggagcaagacagtgggctggtgaattaccagatctctgt
caagggcagtaacctgttcaagttggaagtgcgtcttttg
gatgcagaaaacaaagtcgtggcgaatgggactgggaccc
agggccaacttaaggtgccaggtgtcagcctctggtggcc
gtacctgatgcacgaacgccctgcctatctgtattcattg
gaggtgcagctgactgcacagacgtcactggggcctgtgt
ctgacttctacacactccctgtggggatccgcactgtggc
tgtcaccaagagccagttcctcatcaatgggaaacctttc
tatttccacggtgtcaacaagcatgaggatgcggacatcc
gagggaagggcttcgactggccgctgctggtgaaggactt
caacctgcttcgctggcttggtgccaacgctttccgtacc
agccactacccctatgcagaggaagtgatgcagatgtgtg
accgctatgggattgtggtcatcgatgagtgtcccggcgt
gggcctggcgctgccgcagttcttcaacaacgtttctctg
catcaccacatgcaggtgatggaagaagtggtgcgtaggg
acaagaaccaccccgcggtcgtgatgtggtctgtggccaa
cgagcctgcgtcccacctagaatctgctggctactacttg
aagatggtgatcgctcacaccaaatccttggacccctccc
ggcctgtgacctttgtgagcaactctaactatgcagcaga
caagggggctccgtatgtggatgtgatctgtttgaacagc
tactactcttggtatcacgactacgggcacctggagttga
ttcagctgcagctggccacccagtttgagaactggtataa
gaagtatcagaagcccattattcagagcgagtatggagca
gaaacgattgcagggtttcaccaggatccacctctgatgt
tcactgaagagtaccagaaaagtctgctagagcagtacca
tctgggtctggatcaaaaacgcagaaaatacgtggttgga
gagctcatttggaattttgccgatttcatgactgaacagt
caccgacgagagtgctggggaataaaaaggggatcttcac
tcggcagagacaaccaaaaagtgcagcgttccttttgcga
gagagatactggaagattgccaatgaaaccaggtatcccc
actcagtagccaagtcacaatgtttggaaaacagcctgtt
tacttgagcaagactgataccacctgcgtgtcccttcctc
cccgagtcagggcgacttccacagcagcagaacaagtgcc
tcctggactgttcacggcagaccagaacgtttctggcctg
ggttttgtggtcatctattctagcagggaacactaaaggt
ggaaataaaagattttctattatggaaataaagagttggc
atgaaagtggctactgaaaaaaaaaaaaaaaaaaaaaaaa
a
RPLP0 NM_001002.3 gtctgacgggcgatggcgcagccaatagacaggagcgcta 22
tccgcggtttctgattggctactttgttcgcattataaaa
ggcacgcgcgggcgcgaggcccttctctcgccaggcgtcc
tcgtggaagtgacatcgtctttaaaccctgcgtggcaatc
cctgacgcaccgccgtgatgcccagggaagacagggcgac
ctggaagtccaactacttccttaagatcatccaactattg
gatgattatccgaaatgtttcattgtgggagcagacaatg
tgggctccaagcagatgcagcagatccgcatgtcccttcg
cgggaaggctgtggtgctgatgggcaagaacaccatgatg
cgcaaggccatccgagggcacctggaaaacaacccagctc
tggagaaactgctgcctcatatccgggggaatgtgggctt
tgtgttcaccaaggaggacctcactgagatcagggacatg
ttgctggccaataaggtgccagctgctgcccgtgctggtg
ccattgccccatgtgaagtcactgtgccagcccagaacac
tggtctcgggcccgagaagacctcctttttccaggcttta
ggtatcaccactaaaatctccaggggcaccattgaaatcc
tgagtgatgtgcagctgatcaagactggagacaaagtggg
agccagcgaagccacgctgctgaacatgctcaacatctcc
cccttctcctttgggctggtcatccagcaggtgttcgaca
atggcagcatctacaaccctgaagtgcttgatatcacaga
ggaaactctgcattctcgcttcctggagggtgtccgcaat
gttgccagtgtctgtctgcagattggctacccaactgttg
catcagtaccccattctatcatcaacgggtacaaacgagt
cctggccttgtctgtggagacggattacaccttcccactt
gctgaaaaggtcaaggccttcttggctgatccatctgcct
ttgtggctgctgcccctgtggctgctgccaccacagctgc
tcctgctgctgctgcagccccagctaaggttgaagccaag
gaagagtcggaggagtcggacgaggatatgggatttggtc
tctttgactaatcaccaaaaagcaaccaacttagccagtt
ttatttgcaaaacaaggaaataaaggcttacttctttaaa
aagtaaaaaaaaaaaaaaaaaaaaaaaaa
TFRC NM_003234.3 agagcgtcgggatatcgggtggcggctcgggacggaggac 23
gcgctagtgtgagtgcgggcttctagaactacaccgaccc
tcgtgtcctcccttcatcctgcggggctggctggagcggc
cgctccggtgctgtccagcagccatagggagccgcacggg
gagcgggaaagcggtcgcggccccaggcggggcggccggg
atggagcggggccgcgagcctgtggggaaggggctgtggc
ggcgcctcgagcggctgcaggttcttctgtgtggcagttc
agaatgatggatcaagctagatcagcattctctaacttgt
ttggtggagaaccattgtcatatacccggttcagcctggc
tcggcaagtagatggcgataacagtcatgtggagatgaaa
cttgctgtagatgaagaagaaaatgctgacaataacacaa
aggccaatgtcacaaaaccaaaaaggtgtagtggaagtat
ctgctatgggactattgctgtgatcgtctttttcttgatt
ggatttatgattggctacttgggctattgtaaaggggtag
aaccaaaaactgagtgtgagagactggcaggaaccgagtc
tccagtgagggaggagccaggagaggacttccctgcagca
cgtcgcttatattgggatgacctgaagagaaagttgtcgg
agaaactggacagcacagacttcaccggcaccatcaagct
gctgaatgaaaattcatatgtccctcgtgaggctggatct
caaaaagatgaaaatcttgcgttgtatgttgaaaatcaat
ttcgtgaatttaaactcagcaaagtctggcgtgatcaaca
ttttgttaagattcaggtcaaagacagcgctcaaaactcg
gtgatcatagttgataagaacggtagacttgtttacctgg
tggagaatcctgggggttatgtggcgtatagtaaggctgc
aacagttactggtaaactggtccatgctaattttggtact
aaaaaagattttgaggatttatacactcctgtgaatggat
ctatagtgattgtcagagcagggaaaatcacctttgcaga
aaaggttgcaaatgctgaaagcttaaatgcaattggtgtg
ttgatatacatggaccagactaaatttcccattgttaacg
cagaactttcattctttggacatgctcatctggggacagg
tgacccttacacacctggattcccttccttcaatcacact
cagtttccaccatctcggtcatcaggattgcctaatatac
ctgtccagacaatctccagagctgctgcagaaaagctgtt
tgggaatatggaaggagactgtccctctgactggaaaaca
gactctacatgtaggatggtaacctcagaaagcaagaatg
tgaagctcactgtgagcaatgtgctgaaagagataaaaat
tcttaacatctttggagttattaaaggctttgtagaacca
gatcactatgttgtagttggggcccagagagatgcatggg
gccctggagctgcaaaatccggtgtaggcacagctctcct
attgaaacttgcccagatgttctcagatatggtcttaaaa
gatgggtttcagcccagcagaagcattatctttgccagtt
ggagtgctggagactttggatcggttggtgccactgaatg
gctagagggatacctttcgtccctgcatttaaaggctttc
acttatattaatctggataaagcggttcttggtaccagca
acttcaaggtttctgccagcccactgttgtatacgcttat
tgagaaaacaatgcaaaatgtgaagcatccggttactggg
caatttctatatcaggacagcaactgggccagcaaagttg
agaaactcactttagacaatgctgctttccctttccttgc
atattctggaatcccagcagtttctttctgtttttgcgag
gacacagattatccttatttgggtaccaccatggacacct
ataaggaactgattgagaggattcctgagttgaacaaagt
ggcacgagcagctgcagaggtcgctggtcagttcgtgatt
aaactaacccatgatgttgaattgaacctggactatgaga
ggtacaacagccaactgctttcatttgtgagggatctgaa
ccaatacagagcagacataaaggaaatgggcctgagttta
cagtggctgtattctgctcgtggagacttcttccgtgcta
cttccagactaacaacagatttcgggaatgctgagaaaac
agacagatttgtcatgaagaaactcaatgatcgtgtcatg
agagtggagtatcacttcctctctccctacgtatctccaa
aagagtctcctttccgacatgtcttctggggctccggctc
tcacacgctgccagctttactggagaacttgaaactgcgt
aaacaaaataacggtgcttttaatgaaacgctgttcagaa
accagttggctctagctacttggactattcagggagctgc
aaatgccctctctggtgacgtttgggacattgacaatgag
ttttaaatgtgatacccatagcttccatgagaacagcagg
gtagtctggtttctagacttgtgctgatcgtgctaaattt
tcagtagggctacaaaacctgatgttaaaattccatccca
tcatcttggtactactagatgtctttaggcagcagctttt
aatacagggtagataacctgtacttcaagttaaagtgaat
aaccacttaaaaaatgtccatgatggaatattcccctatc
tctagaattttaagtgctttgtaatgggaactgcctcttt
cctgttgttgttaatgaaaatgtcagaaaccagttatgtg
aatgatctctctgaatcctaagggctggtctctgctgaag
gttgtaagtggtcgcttactttgagtgatcctccaacttc
atttgatgctaaataggagataccaggttgaaagaccttc
tccaaatgagatctaagcctttccataaggaatgtagctg
gtttcctcattcctgaaagaaacagttaactttcagaaga
gatgggcttgttttcttgccaatgaggtctgaaatggagg
tccttctgctggataaaatgaggttcaactgttgattgca
ggaataaggccttaatatgttaacctcagtgtcatttatg
aaaagaggggaccagaagccaaagacttagtatattttct
tttcctctgtcccttcccccataagcctccatttagttct
ttgttatttttgtttcttccaaagcacattgaaagagaac
cagtttcaggtgtttagttgcagactcagtttgtcagact
ttaaagaataatatgctgccaaattttggccaaagtgtta
atcttaggggagagctttctgtccttttggcactgagata
tttattgtttatttatcagtgacagagttcactataaatg
gtgtttttttaatagaatataattatcggaagcagtgcct
tccataattatgacagttatactgtcggttttttttaaat
aaaagcagcatctgctaataaaacccaacagatactggaa
gttttgcatttatggtcaacacttaagggttttagaaaac
agccgtcagccaaatgtaattgaataaagttgaagctaag
atttagagatgaattaaatttaattaggggttgctaagaa
gcgagcactgaccagataagaatgctggttttcctaaatg
cagtgaattgtgaccaagttataaatcaatgtcacttaaa
ggctgtggtagtactcctgcaaaattttatagctcagttt
atccaaggtgtaactctaattcccattttgcaaaatttcc
agtacctttgtcacaatcctaacacattatcgggagcagt
gtcttccataatgtataaagaacaaggtagtttttaccta
ccacagtgtctgtatcggagacagtgatctccatatgtta
cactaagggtgtaagtaattatcgggaacagtgtttccca
taattttcttcatgcaatgacatcttcaaagcttgaagat
cgttagtatctaacatgtatcccaactcctataattccct
atcttttagttttagttgcagaaacattttgtggtcatta
agcattgggtgggtaaattcaaccactgtaaaatgaaatt
actacaaaatttgaaatttagcttgggtttttgttacctt
tatggtttctccaggtcctctacttaatgagatagtagca
tacatttataatgtttgctattgacaagtcattttaactt
tatcacattatttgcatgttacctcctataaacttagtgc
ggacaagttttaatccagaattgaccttttgacttaaagc
agagggactttgtatagaaggtttgggggctgtggggaag
gagagtcccctgaaggtctgacacgtctgcctacccattc
gtggtgatcaattaaatgtaggtatgaataagttcgaagc
tccgtgagtgaaccatcattataaacgtgatgatcagctg
tttgtcatagggcagttggaaacggcctcctagggaaaag
ttcatagggtctcttcaggttcttagtgtcacttacctag
atttacagcctcacttgaatgtgtcactactcacagtctc
tttaatcttcagttttatctttaatctcctcttttatctt
ggactgacatttagcgtagctaagtgaaaaggtcatagct
gagattcctggttcgggtgttacgcacacgtacttaaatg
aaagcatgtggcatgttcatcgtataacacaatatgaata
cagggcatgcattttgcagcagtgagtctcttcagaaaac
ccttttctacagttagggttgagttacttcctatcaagcc
agtacgtgctaacaggctcaatattcctgaatgaaatatc
agactagtgacaagctcctggtcttgagatgtcttctcgt
taaggagatgggccttttggaggtaaaggataaaatgaat
gagttctgtcatgattcactattctagaacttgcatgacc
tttactgtgttagctctttgaatgttcttgaaattttaga
ctttctttgtaaacaaatgatatgtccttatcattgtata
aaagctgttatgtgcaacagtgtggagattccttgtctga
tttaataaaatacttaaacactgaaaaaaaaaaa
18S X03205.1 tacctggttgatcctgccagtagcatatgcttgtctcaaa 24
gattaagccatgcatgtctaagtacgcacggccggtacag
tgaaactgcgaatggctcattaaatcagttatggttcctt
tggtcgctcgctcctctcccacttggataactgtggtaat
tctagagctaatacatgccgacgggcgctgacccccttcg
cgggggggatgcgtgcatttatcagatcaaaaccaacccg
gtcagcccctctccggccccggccggggggcgggcgccgg
cggctttggtgactctagataacctcgggccgatcgcacg
ccccccgtggcggcgacgacccattcgaacgtctgcccta
tcaactttcgatggtagtcgccgtgcctaccatggtgacc
acgggtgacggggaatcagggttcgattccggagagggag
cctgagaaacggctaccacatccaaggaaggcagcaggcg
cgcaaattacccactcccgacccggggaggtagtgacgaa
aaataacaatacaggactctttcgaggccctgtaattgga
atgagtccactttaaatcctttaacgaggatccattggag
ggcaagtctggtgccagcagccgcggtaattccagctcca
atagcgtatattaaagttgctgcagttaaaaagctcgtag
ttggatcttgggagcgggcgggcggtccgccgcgaggcga
gccaccgcccgtccccgccccttgcctctcggcgccccct
cgatgctcttagctgagtgtcccgcggggcccgaagcgtt
tactttgaaaaaattagagtgttcaaagcaggcccgagcc
gcctggataccgcagctaggaataatggaataggaccgcg
gttctattttgttggttttcggaactgaggccatgattaa
gagggacggccgggggcattcgtattgcgccgctagaggt
gaaattcttggaccggcgcaagacggaccagagcgaaagc
atttgccaagaatgttttcattaatcaagaacgaaagtcg
gaggttcgaagacgatcagataccgtcgtagttccgacca
taaacgatgccgaccggcgatgcggcggcgttattcccat
gaccegccgggcagcttccgggaaaccaaagtctttgggt
tccggggggagtatggttgcaaagctgaaacttaaaggaa
ttgacggaagggcaccaccaggagtggagcctgcggctta
atttgactcaacacgggaaacctcacccggcccggacacg
gacaggattgacagattgatagctctttctcgattccgtg
ggtggtggtgcatggccgttcttagttggtggagcgattt
gtctggttaattccgataacgaacgagactctggcatgct
aactagttacgcgacccccgagcggtcggcgtcccccaac
ttcttagagggacaagtggcgttcagccacccgagattga
gcaataacaggtctgtgatgcccttagatgtccggggctg
cacgcgcgctacactgactggctcagcgtgtgcctaccct
acgccggcaggcgcgggtaacccgttgaaccccattcgtg
atggggatcggggattgcaattattccccatgaacgagga
attcccagtaagtgcgggtcataagcttgcgttgattaag
tccctgccctttgtacacaccgcccgtcgctactaccgat
tggatggtttagtgaggccctcggatcggccccgccgggg
tcggcccacggccctggcggagcgctgagaagacggtcga
acttgactatctagaggaagtaaaagtcgtaacaaggttt
ccgtaggtgaacctgcggaaggatcatta
PPIA NM_021130.4 ggggccgaacgtggtataaaaggggcgggaggccaggctc 25
gtgccgttttgcagacgccaccgccgaggaaaaccgtgta
ctattagccatggtcaaccccaccgtgttcttcgacattg
ccgtcgacggcgagcccttgggccgcgtctcctttgagct
gtttgcagacaaggtcccaaagacagcagaaaattttcgt
gctctgagcactggagagaaaggatttggttataagggtt
cctgctttcacagaattattccagggtttatgtgtcaggg
tggtgacttcacacgccataatggcactggtggcaagtcc
atctatggggagaaatttgaagatgagaacttcatcctaa
agcatacgggtcctggcatcttgtccatggcaaatgctgg
acccaacacaaatggttcccagtttttcatctgcactgcc
aagactgagtggttggatggcaagcatgtggtgtttggca
aagtgaaagaaggcatgaatattgtggaggccatggagcg
ctttgggtccaggaatggcaagaccagcaagaagatcacc
attgctgactgtggacaactcgaataagtttgacttgtgt
tttatcttaaccaccagatcattccttctgtagctcagga
gagcacccctccaccccatttgctcgcagtatcctagaat
ctttgtgctctcgctgcagttccctttgggttccatgttt
tccttgttccctcccatgcctagctggattgcagagttaa
gtttatgattatgaaataaaaactaaataacaattgtcct
cgtttgagttaagagtgttgatgtaggctttattttaagc
agtaatgggttacttctgaaacatcacttgtttgcttaat
tctacacagtacttagattttttttactttccagtcccag
gaagtgtcaatgtttgttgagtggaatattgaaaatgtag
gcagcaactgggcatggtggctcactgtctgtaatgtatt
acctgaggcagaagaccacctgagggtaggagtcaagatc
agcctgggcaacatagtgagacgctgtctctacaaaaaat
aattagcctggcctggtggtgcatgcctagtcctagctga
tctggaggctgacgtgggaggattgcttgagcctagagtg
agctattatcatgccactgtacagcctgggtgttcacaga
tcttgtgtctcaaaggtaggcagaggcaggaaaagcaagg
agccagaattaagaggttgggtcagtctgcagtgagttca
tgcatttagaggtgttcttcaagatgactaatgtcaaaaa
ttgagacatctgttgcggttttttttttttttttttcccc
tggaatgcagtggcgtgatctcagctcactgcagcctccg
cctcctgggttcaagtgattctagtgcctcagcctcctga
gtagctgggataatgggcgtgtgccaccatgcccagctaa
tttttgtatttttagtatagatggggtttcatcattttga
ccaggctggtctcaaactcttgacctcagctgatgcgcct
gccttggcctcccaaactgctgagattacagatgtgagcc
accgcaccctacctcattttctgtaacaaagctaagcttg
aacactgttgatgttcttgagggaagcatattgggcttta
ggctgtaggtcaagtttatacatcttaattatggtggaat
tcctatgtagagtctaaaaagccaggtacttggtgctaca
gtcagtctccctgcagagggttaaggcgcagactacctgc
agtgaggaggtactgcttgtagcatatagagcctctccct
agctttggttatggaggctttgaggttttgcaaacctgac
caatttaagccataagatctggtcaaagggatacccttcc
cactaaggacttggtttctcaggaaattatatgtacagtg
cttgctggcagttagatgtcaggacaatctaagctgagaa
aaccccttctctgcccaccttaacagacctctagggttct
taacccagcaatcaagtttgcctatcctagaggtggcgga
tttgatcatttggtgtgttgggcaatttttgttttactgt
ctggttccttctgcgtgaattaccaccaccaccacttgtg
catctcagtcttgtgtgttgtctggttacgtattccctgg
gtgataccattcaatgtcttaatgtacttgtggctcagac
ctgagtgcaaggtggaaataaacatcaaacatcttttcat
tatcccta
PGK1 NM_000291.3 gagagcagcggccgggaaggggcggtgcgggaggcggggt 26
gtggggcggtagtgtgggccctgttcctgcccgcgcggtg
ttccgcattctgcaagcctccggagcgcacgtcggcagtc
ggctccctcgttgaccgaatcaccgacctctctccccagc
tgtatttccaaaatgtcgctttctaacaagctgacgctgg
acaagctggacgttaaagggaagcgggtcgttatgagagt
cgacttcaatgttcctatgaagaacaaccagataacaaac
aaccagaggattaaggctgctgtcccaagcatcaaattct
gcttggacaatggagccaagtcggtagtccttatgagcca
cctaggccggcctgatggtgtgcccatgcctgacaagtac
tccttagagccagttgctgtagaactcaaatctctgctgg
gcaaggatgttctgttcttgaaggactgtgtaggcccaga
agtggagaaagcctgtgccaacccagctgctgggtctgtc
atcctgctggagaacctccgctttcatgtggaggaagaag
ggaagggaaaagatgcttctgggaacaaggttaaagccga
gccagccaaaatagaagctttccgagcttcactttccaag
ctaggggatgtctatgtcaatgatgcttttggcactgctc
acagagcccacagctccatggtaggagtcaatctgccaca
gaaggctggtgggtttttgatgaagaaggagctgaactac
tttgcaaaggccttggagagcccagagcgacccttcctgg
ccatcctgggcggagctaaagttgcagacaagatccagct
catcaataatatgctggacaaagtcaatgagatgattatt
ggtggtggaatggcttttaccttccttaaggtgctcaaca
acatggagattggcacttctctgtttgatgaagagggagc
caagattgtcaaagacctaatgtccaaagctgagaagaat
ggtgtgaagattaccttgcctgttgactttgtcactgctg
acaagtttgatgagaatgccaagactggccaagccactgt
ggcttctggcatacctgctggctggatgggcttggactgt
ggtcctgaaagcagcaagaagtatgctgaggctgtcactc
gggctaagcagattgtgtggaatggtcctgtgggggtatt
tgaatgggaagcttttgcccggggaaccaaagctctcatg
gatgaggtggtgaaagccacttctaggggctgcatcacca
tcataggtggtggagacactgccacttgctgtgccaaatg
gaacacggaggataaagtcagccatgtgagcactgggggt
ggtgccagtttggagctcctggaaggtaaagtccttcctg
gggtggatgctctcagcaatatttagtactttcctgcctt
ttagttcctgtgcacagcccctaagtcaacttagcatttt
ctgcatctccacttggcattagctaaaaccttccatgtca
agattcagctagtggccaagagatgcagtgccaggaaccc
ttaaacagttgcacagcatctcagctcatcttcactgcac
cctggatttgcatacattcttcaagatcccatttgaattt
tttagtgactaaaccattgtgcattctagagtgcatatat
ttatattttgcctgttaaaaagaaagtgagcagtgttagc
ttagttctcttttgatgtaggttattatgattagctttgt
cactgtttcactactcagcatggaaacaagatgaaattcc
atttgtaggtagtgagacaaaattgatgatccattaagta
aacaataaaagtgtccattgaaaccgtgattttttttttt
ttcctgtcatactttgttaggaagggtgagaatagaatct
tgaggaacggatcagatgtctatattgctgaatgcaagaa
gtggggcagcagcagtggagagatgggacaattagataaa
tgtccattctttatcaagggcctactttatggcagacatt
gtgctagtgcttttattctaacttttatttttatcagtta
cacatgatcataatttaaaaagtcaaggcttataacaaaa
aagccccagcccattcctcccattcaagattcccactccc
cagaggtgaccactttcaactcttgagtttttcaggtata
tacctccatgtttctaagtaatatgcttatattgttcact
tcttttttttttattttttaaagaaatctatttcatacca
tggaggaaggctctgttccacatatatttccacttcttca
ttctctcggtatagttttgtcacaattatagattagatca
aaagtctacataactaatacagctgagctatgtagtatgc
tatgattaaatttacttatgtaaaaaaaaaaaaaaaaaa
RPL13A NM_012423.3 cacttctgccgcccctgtttcaagggataagaaaccctgc 27
gacaaaacctcctccttttccaagcggctgccgaagatgg
cggaggtgcaggtcctggtgcttgatggtcgaggccatct
cctgggccgcctggcggccatcgtggctaaacaggtactg
ctgggccggaaggtggtggtcgtacgctgtgaaggcatca
acatttctggcaatttctacagaaacaagttgaagtacct
ggctttcctccgcaagcggatgaacaccaacccttcccga
ggcccctaccacttccgggcccccagccgcatcttctggc
ggaccgtgcgaggtatgctgccccacaaaaccaagcgagg
ccaggccgctctggaccgtctcaaggtgtttgacggcatc
ccaccgccctacgacaagaaaaagcggatggtggttcctg
ctgccctcaaggtcgtgcgtctgaagcctacaagaaagtt
tgcctatctggggcgcctggctcacgaggttggctggaag
taccaggcagtgacagccaccctggaggagaagaggaaag
agaaagccaagatccactaccggaagaagaaacagctcat
gaggctacggaaacaggccgagaagaacgtggagaagaaa
attgacaaatacacagaggtcctcaagacccacggactcc
tggtctgagcccaataaagactgttaattcctcatgcgtt
gcctgcccttcctccattgttgccctggaatgtacgggac
ccaggggcagcagcagtccaggtgccacaggcagccctgg
gacataggaagctgggagcaaggaaagggtcttagtcact
gcctcccgaagttgcttgaaagcactcggagaattgtgca
ggtgtcatttatctatgaccaataggaagagcaaccagtt
actatgagtgaaagggagccagaagactgattggagggcc
ctatcttgtgagtggggcatctgttggactttccacctgg
tcatatactctgcagctgttagaatgtgcaagcacttggg
gacagcatgagcttgctgttgtacacagggtatttctaga
agcagaaatagactgggaagatgcacaaccaaggggttac
aggcatcgcccatgctcctcacctgtattttgtaatcaga
aataaattgcttttaaagaaaaaaaaaaaaaaaaaa
B2M NM_004048.2 aatataagtggaggcgtcgcgctggcgggcattcctgaag 28
ctgacagcattcgggccgagatgtctcgctccgtggcctt
agctgtgctcgcgctactctctctttctggcctggaggct
atccagcgtactccaaagattcaggtttactcacgtcatc
cagcagagaatggaaagtcaaatttcctgaattgctatgt
gtctgggtttcatccatccgacattgaagttgacttactg
aagaatggagagagaattgaaaaagtggagcattcagact
tgtctttcagcaaggactggtctttctatctcttgtacta
cactgaattcacccccactgaaaaagatgagtatgcctgc
cgtgtgaaccatgtgactttgtcacagcccaagatagtta
agtgggatcgagacatgtaagcagcatcatggaggtttga
agatgccgcatttggattggatgaattccaaattctgctt
gcttgctttttaatattgatatgcttatacacttacactt
tatgcacaaaatgtagggttataataatgttaacatggac
atgatcttctttataattctactttgagtgctgtctccat
gtttgatgtatctgagcaggttgctccacaggtagctcta
ggagggctggcaacttagaggtggggagcagagaattctc
ttatccaacatcaacatcttggtcagatttgaactcttca
atctcttgcactcaaagcttgttaagatagttaagcgtgc
ataagttaacttccaatttacatactctgcttagaatttg
ggggaaaatttagaaatataattgacaggattattggaaa
tttgttataatgaatgaaacattttgtcatataagattca
tatttacttcttatacatttgataaagtaaggcatggttg
tggttaatctggtttatttttgttccacaagttaaataaa
tcataaaacttgatgtgttatctctta
YWHAZ NM_003406.3 ctttctccttccccttcttccgggctcccgtcccggctca 29
tcacccggcctgtggcccactcccaccgccagctggaacc
ctggggactacgacgtccctcaaaccttgcttctaggaga
taaaaagaacatccagtcatggataaaaatgagctggttc
agaaggccaaactggccgagcaggctgagcgatatgatga
catggcagcctgcatgaagtctgtaactgagcaaggagct
gaattatccaatgaggagaggaatcttctctcagttgctt
ataaaaatgttgtaggagcccgtaggtcatcttggagggt
cgtctcaagtattgaacaaaagacggaaggtgctgagaaa
aaacagcagatggctcgagaatacagagagaaaattgaga
cggagctaagagatatctgcaatgatgtactgtctctttt
ggaaaagttcttgatccccaatgcttcacaagcagagagc
aaagtcttctatttgaaaatgaaaggagattactaccgtt
acttggctgaggttgccgctggtgatgacaagaaagggat
tgtcgatcagtcacaacaagcataccaagaagcttttgaa
atcagcaaaaaggaaatgcaaccaacacatcctatcagac
tgggtctggcccttaacttctctgtgttctattatgagat
tctgaactccccagagaaagcctgctctcttgcaaagaca
gcttttgatgaagccattgctgaacttgatacattaagtg
aagagtcatacaaagacagcacgctaataatgcaattact
gagagacaacttgacattgtggacatcggatacccaagga
gacgaagctgaagcaggagaaggaggggaaaattaaccgg
ccttccaacttttgtctgcctcattctaaaatttacacag
tagaccatttgtcatccatgctgtcccacaaatagttttt
tgtttacgatttatgacaggtttatgttacttctatttga
atttctatatttcccatgtggtttttatgtttaatattag
gggagtagagccagttaacatttagggagttatctgtttt
catcttgaggtggccaatatggggatgtggaatttttata
caagttataagtgtttggcatagtacttttggtacattgt
ggcttcaaaagggccagtgtaaaactgcttccatgtctaa
gcaaagaaaactgcctacatactggtttgtcctggcgggg
aataaaagggatcattggttccagtcacaggtgtagtaat
tgtgggtactttaaggtttggagcacttacaaggctgtgg
tagaatcataccccatggataccacatattaaaccatgta
tatctgtggaatactcaatgtgtacacctttgactacagc
tgcagaagtgttcctttagacaaagttgtgacccatttta
ctctggataagggcagaaacggttcacattccattatttg
taaagttacctgctgttagctttcattatttttgctacac
tcattttatttgtatttaaatgttttaggcaacctaagaa
caaatgtaaaagtaaagatgcaggaaaaatgaattgcttg
gtattcattacttcatgtatatcaagcacagcagtaaaac
aaaaacccatgtatttaacttttttttaggatttttgctt
ttgtgatttttttttttttgatacttgcctaacatgcatg
tgctgtaaaaatagttaacagggaaataacttgagatgat
ggctagctttgtttaatgtcttatgaaattttcatgaaca
atccaagcataattgttaagaacacgtgtattaaattcat
gtaagtggaataaaagttttatgaatggacttttcaacta
ctttctctacagcttttcatgtaaattagtcttggttctg
aaacttctctaaaggaaattgtacattttttgaaatttat
tccttattccctcttggcagctaatgggctcttaccaagt
ttaaacacaaaatttatcataacaaaaatactactaatat
aactactgtttccatgtcccatgatcccctctcttcctcc
ccaccctgaaaaaaatgagttcctattttttctgggagag
ggggggattgattagaaaaaaatgtagtgtgttccattta
aaattttggcatatggcattttctaacttaggaagccaca
atgttcttggcccatcatgacattgggtagcattaactgt
aagttttgtgcttccaaatcactttttggtttttaagaat
ttcttgatactcttatagcctgccttcaattttgatcctt
tattctttctatttgtcaggtgcacaagattaccttcctg
ttttagccttctgtcttgtcaccaaccattcttacttggt
ggccatgtacttggaaaaaggccgcatgatctttctggct
ccactcagtgtctaaggcaccctgcttcctttgcttgcat
cccacagactatttccctcatcctatttactgcagcaaat
ctctccttagttgatgagactgtgtttatctccctttaaa
accctacctatcctgaatggtctgtcattgtctgccttta
aaatccttcctctttcttcctcctctattctctaaataat
gatggggctaagttatacccaaagctcactttacaaaata
tttcctcagtactttgcagaaaacaccaaacaaaaatgcc
attttaaaaaaggtgtattttttcttttagaatgtaagct
cctcaagagcagggacaatgttttctgtatgttctattgt
gcctagtacactgtaaatgctcaataaatattgatgatgg
gaggcagtgagtcttgatgataagggtgagaaactgaaat
cccaaacactgttttgttgcttgttttattatgacctcag
attaaattgggaaatattggcccttttgaataattgtccc
aaatattacattcaaataaaagtgcaatggagaaaaaaaa
aaa
SDHA NM_004168.3 actgcagccccgctcgactccggcgtggtgcgcaggcgcg 30
gtatcccccctcccccgccagctcgaccccggtgtggtgc
gcaggcgcagtctgcgcagggactggcgggactgcgcggc
ggcaacagcagacatgtcgggggtccggggcctgtcgcgg
ctgctgagcgctcggcgcctggcgctggccaaggcgtggc
caacagtgttgcaaacaggaacccgaggttttcacttcac
tgttgatgggaacaagagggcatctgctaaagtttcagat
tccatttctgctcagtatccagtagtggatcatgaatttg
atgcagtggtggtaggcgctggaggggcaggcttgcgagc
tgcatttggcctttctgaggcagggtttaatacagcatgt
gttaccaagctgtttcctaccaggtcacacactgttgcag
cacagggaggaatcaatgctgctctggggaacatggagga
ggacaactggaggtggcatttctacgacaccgtgaagggc
tccgactggctgggggaccaggatgccatccactacatga
cggagcaggcccccgccgccgtggtcgagctagaaaatta
tggcatgccgtttagcagaactgaagatgggaagatttat
cagcgtgcatttggtggacagagcctcaagtttggaaagg
gcgggcaggcccatcggtgctgctgtgtggctgatcggac
tggccactcgctattgcacaccttatatggaaggtctctg
cgatatgataccagctattttgtggagtattttgccttgg
atctcctgatggagaatggggagtgccgtggtgtcatcgc
actgtgcatagaggacgggtccatccatcgcataagagca
aagaacactgttgttgccacaggaggctacgggcgcacct
acttcagctgcacgtctgcccacaccagcactggcgacgg
cacggccatgatcaccagggcaggccttccttgccaggac
ctagagtttgttcagttccaccctacaggcatatatggtg
ctggttgtctcattacggaaggatgtcgtggagagggagg
cattctcattaacagtcaaggcgaaaggtttatggagcga
tacgcccctgtcgcgaaggacctggcgtctagagatgtgg
tgtctcggtccatgactctggagatccgagaaggaagagg
ctgtggccctgagaaagatcacgtctacctgcagctgcac
cacctacctccagagcagctggccacgcgcctgcctggca
tttcagagacagccatgatcttcgctggcgtggacgtcac
gaaggagccgatccctgtcctccccaccgtgcattataac
atgggcggcattcccaccaactacaaggggcaggtcctga
ggcacgtgaatggccaggatcagattgtgcccggcctgta
cgcctgtggggaggccgcctgtgcctcggtacatggtgcc
aaccgcctcggggcaaactcgctcttggacctggttgtct
ttggtcgggcatgtgccctgagcatcgaagagtcatgcag
gcctggagataaagtccctccaattaaaccaaacgctggg
gaagaatctgtcatgaatcttgacaaattgagatttgctg
atggaagcataagaacatcggaactgcgactcagcatgca
gaagtcaatgcaaaatcatgctgccgtgttccgtgtggga
agcgtgttgcaagaaggttgtgggaaaatcagcaagctct
atggagacctaaagcacctgaagacgttcgaccggggaat
ggtctggaacacggacctggtggagaccctggagctgcag
aacctgatgctgtgtgcgctgcagaccatctacggagcag
aggcacggaaggagtcacggggcgcgcatgccagggaaga
ctacaaggtgcggattgatgagtacgattactccaagccc
atccaggggcaacagaagaagccctttgaggagcactgga
ggaagcacaccctgtcctatgtggacgttggcactgggaa
ggtcactctggaatatagacccgtgatcgacaaaactttg
aacgaggctgactgtgccaccgtcccgccagccattcgct
cctactgatgagacaagatgtggtgatgacagaatcagct
tttgtaattatgtataatagctcatgcatgtgtccatgtc
ataactgtcttcatacgcttctgcactctggggaagaagg
agtacattgaagggagattggcacctagtggctgggagct
tgccaggaacccagtggccagggagcgtggcacttacctt
tgtcccttgcttcattcttgtgagatgataaaactgggca
cagctcttaaataaaatataaatgaacaaactttctttta
tttccaaatccatttgaaatattttactgttgtgacttta
gtcatatttgttgacctaaaaatcaaatgtaatctttgta
ttgtgttacatcaaaatccagatattttgtatagtttctt
ttttctttttcttttcttttttttttttgagacaggatcg
gtgcagtagtacaatcacagctcactgcagcctcaaactc
ctgggcagctcaggtgatcttcctgactcagccttctgag
tagttggggctacaggtgtgcaccaccatgcccagctcat
ttattttgtaattgtagggacagggtctcactgtgttgcc
taggctggtctcaagtgatcctccctccttggcctcccaa
ggtgctggaattataggtgtgaacaaaccaaaaaaaaaaa
aaa
HPRT1 NM_000194.2 ggcggggcctgcttctcctcagcttcaggcggctgcgacg 31
agccctcaggcgaacctctcggctttcccgcgcggcgccg
cctcttgctgcgcctccgcctcctcctctgctccgccacc
ggcttcctcctcctgagcagtcagcccgcgcgccggccgg
ctccgttatggcgacccgcagccctggcgtcgtgattagt
gatgatgaaccaggttatgaccttgatttattttgcatac
ctaatcattatgctgaggatttggaaagggtgtttattcc
tcatggactaattatggacaggactgaacgtcttgctcga
gatgtgatgaaggagatgggaggccatcacattgtagccc
tctgtgtgctcaaggggggctataaattctttgctgacct
gctggattacatcaaagcactgaatagaaatagtgataga
tccattcctatgactgtagattttatcagactgaagagct
attgtaatgaccagtcaacaggggacataaaagtaattgg
tggagatgatctctcaactttaactggaaagaatgtcttg
attgtggaagatataattgacactggcaaaacaatgcaga
ctttgctttccttggtcaggcagtataatccaaagatggt
caaggtcgcaagcttgctggtgaaaaggaccccacgaagt
gttggatataagccagactttgttggatttgaaattccag
acaagtttgttgtaggatatgcccttgactataatgaata
cttcagggatttgaatcatgtttgtgtcattagtgaaact
ggaaaagcaaaatacaaagcctaagatgagagttcaagtt
gagtttggaaacatctggagtcctattgacatcgccagta
aaattatcaatgttctagttctgtggccatctgcttagta
gagctttttgcatgtatcttctaagaattttatctgtttt
gtactttagaaatgtcagttgctgcattcctaaactgttt
atttgcactatgagcctatagactatcagttccctttggg
cggattgttgtttaacttgtaaatgaaaaaattctcttaa
accacagcactattgagtgaaacattgaactcatatctgt
aagaaataaagagaagatatattagttttttaattggtat
tttaatttttatatatgcaggaaagaatagaagtgattga
atattgttaattataccaccgtgtgttagaaaagtaagaa
gcagtcaattttcacatcaaagacagcatctaagaagttt
tgttctgtcctggaattattttagtagtgtttcagtaatg
ttgactgtattttccaacttgttcaaattattaccagtga
atctttgtcagcagttcccttttaaatgcaaatcaataaa
ttcccaaaaatttaaaaaaaaaaaaaaaaaaaaaa
Definitions
The articles “a” and “an” are used in this disclosure to refer to one or more than one (i.e., to at least one) of the grammatical object of the article. By way of example, “an element” means one element or more than one element.
The term “and/or” is used in this disclosure to mean either “and” or “or” unless indicated otherwise.
As used herein, the terms “polynucleotide” and “nucleic acid molecule” are used interchangeably to mean a polymeric form of nucleotides of at least 10 bases or base pairs in length, either ribonucleotides or deoxynucleotides or a modified form of either type of nucleotide, and is meant to include single and double stranded forms of DNA. As used herein, a nucleic acid molecule or nucleic acid sequence that serves as a probe in a microarray analysis preferably comprises a chain of nucleotides, more preferably DNA and/or RNA. In other aspects, a nucleic acid molecule or nucleic acid sequence comprises other kinds of nucleic acid structures such a for instance a DNA/RNA helix, peptide nucleic acid (PNA), locked nucleic acid (LNA) and/or a ribozyme. Hence, as used herein the term “nucleic acid molecule” also encompasses a chain comprising non-natural nucleotides, modified nucleotides and/or non-nucleotide building blocks which exhibit the same function as natural nucleotides.
As used herein, the terms “hybridize,” “hybridizing”, “hybridizes,” and the like, used in the context of polynucleotides, are meant to refer to conventional hybridization conditions, such as hybridization in 50% formamide/6×SSC/0.1% SDS/100 μg/ml ssDNA, in which temperatures for hybridization are above 37 degrees centigrade and temperatures for washing in 0.1×SSC/0.1% SDS are above 55 degrees C., and preferably to stringent hybridization conditions.
As used herein, the term “normalization” or “normalizer” refers to the expression of a differential value in terms of a standard value to adjust for effects which arise from technical variation due to sample handling, sample preparation, and measurement methods rather than biological variation of biomarker concentration in a sample. For example, when measuring the expression of a differentially expressed protein, the absolute value for the expression of the protein can be expressed in terms of an absolute value for the expression of a standard protein that is substantially constant in expression.
The terms “diagnosis” and “diagnostics” also encompass the terms “prognosis” and “prognostics”, respectively, as well as the applications of such procedures over two or more time points to monitor the diagnosis and/or prognosis over time, and statistical modeling based thereupon. Furthermore, the term diagnosis includes: a. prediction (determining if a patient will likely develop aggressive disease (hyperproliferative/invasive)), b. prognosis (predicting whether a patient will likely have a better or worse outcome at a pre-selected time in the future), c. therapy selection, d. therapeutic drug monitoring, and e. relapse monitoring.
“Accuracy” refers to the degree of conformity of a measured or calculated quantity (a test reported value) to its actual (or true) value. Clinical accuracy relates to the proportion of true outcomes (true positives (TP) or true negatives (TN)) versus misclassified outcomes (false positives (FP) or false negatives (FN)), and may be stated as a sensitivity, specificity, positive predictive values (PPV) or negative predictive values (NPV), or as a likelihood, odds ratio, among other measures.
The term “biological sample” as used herein refers to any sample of biological origin potentially containing one or more biomarkers. Examples of biological samples include tissue, organs, or bodily fluids such as whole blood, plasma, serum, tissue, lavage or any other specimen used for detection of disease.
The term “subject” as used herein refers to a mammal, preferably a human. In some aspects, a subject can have at least one colon cancer symptom. In some aspects, a subject can have a predisposition or familial history for developing a colon cancer. A subject can also have been previously diagnosed with a colon cancer and is tested for cancer recurrence.
“Treating” or “treatment” as used herein with regard to a condition may refer to preventing the condition, slowing the onset or rate of development of the condition, reducing the risk of developing the condition, preventing or delaying the development of symptoms associated with the condition, reducing or ending symptoms associated with the condition, generating a complete or partial regression of the condition, or some combination thereof.
Biomarker levels may change due to treatment of the disease. The changes in biomarker levels may be measured by the present disclosure. Changes in biomarker levels may be used to monitor the progression of disease or therapy.
“Altered”, “changed” or “significantly different” refer to a detectable change or difference from a reasonably comparable state, profile, measurement, or the like. Such changes may be all or none. They may be incremental and need not be linear. They may be by orders of magnitude. A change may be an increase or decrease by 5%, 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, 90%, 95%, 99%, 100%, or more, or any value in between 0% and 100%. Alternatively, the change may be 1-fold, 1.5-fold, 2-fold, 3-fold, 4-fold, 5-fold or more, or any values in between 1-fold and five-fold. The change may be statistically significant with a p value of 0.1, 0.05, 0.001, or 0.0001.
The term “stable disease” refers to a diagnosis for the presence of a colon cancer, however the colon cancer has been treated and remains in a stable condition, i.e. one that that is not progressive, as determined by imaging data and/or best clinical judgment.
The term “progressive disease” refers to a diagnosis for the presence of a highly active state of a colon cancer, i.e. one has not been treated and is not stable or has been treated and has not responded to therapy, or has been treated and active disease remains, as determined by imaging data and/or best clinical judgment.
The term “neoplastic disease” refers to any abnormal growth of cells or tissues being either benign (non-cancerous) or malignant (cancerous). For example, the neoplastic disease can be a colon cancer.
The term “neoplastic tissue” refers to a mass of cells that grow abnormally.
The term “non-neoplastic tissue” refers to a mass of cells that grow normally.
The term “immunotherapy” can refer to activating immunotherapy or suppressing immunotherapy. As will be appreciated by those in the art, activating immunotherapy refers to the use of a therapeutic agent that induces, enhances, or promotes an immune response, including, e.g., a T cell response while suppressing immunotherapy refers to the use of a therapeutic agent that interferes with, suppresses, or inhibits an immune response, including, e.g., a T cell response. Activating immunotherapy may comprise the use of checkpoint inhibitors. Activating immunotherapy may comprise administering to a subject a therapeutic agent that activates a stimulatory checkpoint molecule. Stimulatory checkpoint molecules include, but are not limited to, CD27, CD28, CD40, CD122, CD137, OX40, GITR and ICOS. Therapeutic agents that activate a stimulatory checkpoint molecule include, but are not limited to, MEDI0562, TGN1412, CDX-1127, lipocalin.
The term “antibody” herein is used in the broadest sense and encompasses various antibody structures, including but not limited to monoclonal antibodies, polyclonal antibodies, multispecific antibodies (e.g., bispecific antibodies), and antibody fragments so long as they exhibit the desired antigen-binding activity. An antibody that binds to a target refers to an antibody that is capable of binding the target with sufficient affinity such that the antibody is useful as a diagnostic and/or therapeutic agent in targeting the target. In one embodiment, the extent of binding of an anti-target antibody to an unrelated, non-target protein is less than about 10% of the binding of the antibody to target as measured, e.g., by a radioimmunoassay (RIA) or biacore assay. In certain embodiments, an antibody that binds to a target has a dissociation constant (Kd) of <1 μM, <100 nM, <10 nM, <1 nM, <0.1 nM, <0.01 nM, or <0.001 nM (e.g. 108 M or less, e.g. from 108 M to 1013 M, e.g., from 109 M to 1013 M). In certain embodiments, an anti-target antibody binds to an epitope of a target that is conserved among different species.
A “blocking antibody” or an “antagonist antibody” is one that partially or fully blocks, inhibits, interferes, or neutralizes a normal biological activity of the antigen it binds. For example, an antagonist antibody may block signaling through an immune cell receptor (e.g., a T cell receptor) so as to restore a functional response by T cells (e.g., proliferation, cytokine production, target cell killing) from a dysfunctional state to antigen stimulation.
An “agonist antibody” or “activating antibody” is one that mimics, promotes, stimulates, or enhances a normal biological activity of the antigen it binds. Agonist antibodies can also enhance or initiate signaling by the antigen to which it binds. In some embodiments, agonist antibodies cause or activate signaling without the presence of the natural ligand. For example, an agonist antibody may increase memory T cell proliferation, increase cytokine production by memory T cells, inhibit regulatory T cell function, and/or inhibit regulatory T cell suppression of effector T cell function, such as effector T cell proliferation and/or cytokine production.
An “antibody fragment” refers to a molecule other than an intact antibody that comprises a portion of an intact antibody that binds the antigen to which the intact antibody binds. Examples of antibody fragments include but are not limited to Fv, Fab, Fab′, Fab′-SH, F(ab′)2; diabodies; linear antibodies; single-chain antibody molecules (e.g. scFv); and multispecific antibodies formed from antibody fragments.
Administering chemotherapy to a subject can comprise administering a therapeutically effective dose of at least one chemotherapeutic agent. Chemotherapeutic agents include, but are not limited to, 13-cis-Retinoic Acid, 2-CdA, 2-Chlorodeoxyadenosine, 5-Azacitidine, 5-Fluorouracil, 5-FU, 6-Mercaptopurine, 6-MP, 6-TG, 6-Thioguanine, Abemaciclib, Abiraterone acetate, Abraxane, Accutane, Actinomycin-D, Adcetris, Ado-Trastuzumab Emtansine, Adriamycin, Adrucil, Afatinib, Afinitor, Agrylin, Ala-Cort, Aldesleukin, Alemtuzumab, Alecensa, Alectinib, Alimta, Alitretinoin, Alkaban-AQ, Alkeran, All-transretinoic Acid, Alpha Interferon, Altretamine, Alunbrig, Amethopterin, Amifostine, Aminoglutethimide, Anagrelide, Anandron, Anastrozole, Apalutamide, Arabinosylcytosine, Ara-C, Aranesp, Aredia, Arimidex, Aromasin, Arranon, Arsenic Trioxide, Arzerra, Asparaginase, Atezolizumab, Atra, Avastin, Avelumab, Axicabtagene Ciloleucel, Axitinib, Azacitidine, Bavencio, Bcg, Beleodaq, Belinostat, Bendamustine, Bendeka, Besponsa, Bevacizumab, Bexarotene, Bexxar, Bicalutamide, Bicnu, Blenoxane, Bleomycin, Blinatumomab, Blincyto, Bortezomib, Bosulif, Bosutinib, Brentuximab Vedotin, Brigatinib, Busulfan, Busulfex, C225, Cabazitaxel, Cabozantinib, Calcium Leucovorin, Campath, Camptosar, Camptothecin-11, Capecitabine, Caprelsa, Carac, Carboplatin, Carfilzomib, Carmustine, Carmustine Wafer, Casodex, CCI-779, Ccnu, Cddp, Ceenu, Ceritinib, Cerubidine, Cetuximab, Chlorambucil, Cisplatin, Citrovorum Factor, Cladribine, Clofarabine, Clolar, Cobimetinib, Cometriq, Cortisone, Cosmegen, Cotellic, Cpt-11, Crizotinib, Cyclophosphamide, Cyramza, Cytadren, Cytarabine, Cytarabine Liposomal, Cytosar-U, Cytoxan, Dabrafenib, Dacarbazine, Dacogen, Dactinomycin, Daratumumab, Darbepoetin Alfa, Darzalex, Dasatinib, Daunomycin, Daunorubicin, Daunorubicin Cytarabine (Liposomal), daunorubicin-hydrochloride, Daunorubicin Liposomal, DaunoXome, Decadron, Decitabine, Degarelix, Delta-Cortef, Deltasone, Denileukin Diftitox, Denosumab, DepoCyt, Dexamethasone, Dexamethasone Acetate, Dexamethasone Sodium Phosphate, Dexasone, Dexrazoxane, Dhad, Dic, Diodex, Docetaxel, Doxil, Doxorubicin, Doxorubicin Liposomal, Droxia, DTIC, Dtic-Dome, Duralone, Durvalumab, Eculizumab, Efudex, Ellence, Elotuzumab, Eloxatin, Elspar, Eltrombopag, Emcyt, Empliciti, Enasidenib, Enzalutamide, Epirubicin, Epoetin Alfa, Erbitux, Eribulin, Erivedge, Erleada, Erlotinib, Erwinia L-asparaginase, Estramustine, Ethyol, Etopophos, Etoposide, Etoposide Phosphate, Eulexin, Everolimus, Evista, Exemestane, Fareston, Farydak, Faslodex, Femara, Filgrastim, Firmagon, Floxuridine, Fludara, Fludarabine, Fluoroplex, Fluorouracil, Fluorouracil (cream), Fluoxymesterone, Flutamide, Folinic Acid, Folotyn, Fudr, Fulvestrant, G-Csf, Gazyva, Gefitinib, Gemcitabine, Gemtuzumab ozogamicin, Gemzar, Gilotrif, Gleevec, Gleostine, Gliadel Wafer, Gm-Csf, Goserelin, Granix, Granulocyte—Colony Stimulating Factor, Granulocyte Macrophage Colony Stimulating Factor, Halaven, Halotestin, Herceptin, Hexadrol, Hexalen, Hexamethylmelamine, Hmm, Hycamtin, Hydrea, Hydrocort Acetate, Hydrocortisone, 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Mechlorethamine Hydrochloride, Medralone, Medrol, Megace, Megestrol, Megestrol Acetate, Mekinist, Mercaptopurine, Mesna, Mesnex, Methotrexate, Methotrexate Sodium, Methylprednisolone, Meticorten, Midostaurin, Mitomycin, Mitomycin-C, Mitoxantrone, M-Prednisol, MTC, MTX, Mustargen, Mustine, Mutamycin, Myleran, Mylocel, Mylotarg, Navelbine, Necitumumab, Nelarabine, Neosar, Neratinib, Nerlynx, Neulasta, Neumega, Neupogen, Nexavar, Nilandron, Nilotinib, Nilutamide, Ninlaro, Nipent, Niraparib, Nitrogen Mustard, Nivolumab, Nolvadex, Novantrone, Nplate, Obinutuzumab, Octreotide, Octreotide Acetate, Odomzo, Ofatumumab, Olaparib, Olaratumab, Omacetaxine, Oncospar, Oncovin, Onivyde, Ontak, Onxal, Opdivo, Oprelvekin, Orapred, Orasone, Osimertinib, Otrexup, Oxaliplatin, Paclitaxel, Paclitaxel Protein-bound, Palbociclib, Pamidronate, Panitumumab, Panobinostat, Panretin, Paraplatin, Pazopanib, Pediapred, Peg Interferon, Pegaspargase, Pegfilgrastim, Peg-Intron, PEG-L-asparaginase, Pembrolizumab, Pemetrexed, Pentostatin, Perj eta, Pertuzumab, Phenylalanine Mustard, Platinol, Platinol-AQ, Pomalidomide, Pomalyst, Ponatinib, Portrazza, Pralatrexate, Prednisolone, Prednisone, Prelone, Procarbazine, Procrit, Proleukin, Prolia, Prolifeprospan 20 with Carmustine Implant, Promacta, Provenge, Purinethol, Radium 223 Dichloride, Raloxifene, Ramucirumab, Rasuvo, Regorafenib, Revlimid, Rheumatrex, Ribociclib, Rituxan, Rituxan Hycela, Rituximab, Rituximab Hyalurodinase, Roferon-A (Interferon Alfa-2a), Romidepsin, Romiplostim, Rubex, Rubidomycin Hydrochloride, Rubraca, Rucaparib, Ruxolitinib, Rydapt, Sandostatin, Sandostatin LAR, Sargramostim, Siltuximab, Sipuleucel-T, Soliris, Solu-Cortef, Solu-Medrol, Somatuline, Sonidegib, Sorafenib, Sprycel, Sti-571, Stivarga, Streptozocin, SU11248, Sunitinib, Sutent, Sylvant, Synribo, Tafinlar, Tagrisso, Talimogene Laherparepvec, Tamoxifen, Tarceva, Targretin, Tasigna, Taxol, Taxotere, Tecentriq, Temodar, Temozolomide, Temsirolimus, Teniposide, Tespa, Thalidomide, Thalomid, TheraCys, Thioguanine, Thioguanine Tabloid, Thiophosphoamide, Thioplex, Thiotepa, Tice, Ti sagenlecleucel, Toposar, Topotecan, Toremifene, Torisel, Tositumomab, Trabectedin, Trametinib, Trastuzumab, Treanda, Trelstar, Tretinoin, Trexall, Trifluridine/Tipiricil, Triptorelin pamoate, Trisenox, Tspa, T-VEC, Tykerb, Valrubicin, Valstar, Vandetanib, VCR, Vectibix, Velban, Velcade, Vemurafenib, Venclexta, Venetoclax, VePesid, Verzenio, Vesanoid, Viadur, Vidaza, Vinblastine, Vinblastine Sulfate, Vincasar Pfs, Vincristine, Vincristine Liposomal, Vinorelbine, Vinorelbine Tartrate, Vismodegib, Vlb, VM-26, Vorinostat, Votrient, VP-16, Vumon, Vyxeos, Xalkori Capsules, Xeloda, Xgeva, Xofigo, Xtandi, Yervoy, Yescarta, Yondelis, Zaltrap, Zanosar, Zarxio, Zejula, Zelboraf, Zevalin, Zinecard, Ziv-aflibercept, Zoladex, Zoledronic Acid, Zolinza, Zometa, Zydelig, Zykadia, Zytiga, or any combination thereof.
The terms “effective amount” and “therapeutically effective amount” of an agent or compound are used in the broadest sense to refer to a nontoxic but sufficient amount of an active agent or compound to provide the desired effect or benefit.
The term “benefit” is used in the broadest sense and refers to any desirable effect and specifically includes clinical benefit as defined herein. Clinical benefit can be measured by assessing various endpoints, e.g., inhibition, to some extent, of disease progression, including slowing down and complete arrest; reduction in the number of disease episodes and/or symptoms; reduction in lesion size; inhibition (i.e., reduction, slowing down or complete stopping) of disease cell infiltration into adjacent peripheral organs and/or tissues; inhibition (i.e. reduction, slowing down or complete stopping) of disease spread; decrease of auto-immune response, which may, but does not have to, result in the regression or ablation of the disease lesion; relief, to some extent, of one or more symptoms associated with the disorder; increase in the length of disease-free presentation following treatment, e.g., progression-free survival; increased overall survival; higher response rate; and/or decreased mortality at a given point of time following treatment.
The terms “cancer” and “cancerous” refer to or describe the physiological condition in mammals that is typically characterized by unregulated cell growth. Included in this definition are benign and malignant cancers. Examples of cancer include but are not limited to, carcinoma, lymphoma, blastoma, sarcoma, and leukemia. More particular examples of such cancers include adrenocortical carcinoma, bladder urothelial carcinoma, breast invasive carcinoma, cervical squamous cell carcinoma, endocervical adenocarcinoma, cholangiocarcinoma, colon adenocarcinoma, lymphoid neoplasm diffuse large B-cell lymphoma, esophageal carcinoma, glioblastoma multiforme, head and neck squamous cell carcinoma, kidney chromophobe, kidney renal clear cell carcinoma, kidney renal papillary cell carcinoma, acute myeloid leukemia, brain lower grade glioma, liver hepatocellular carcinoma, lung adenocarcinoma, lung squamous cell carcinoma, mesothelioma, ovarian serous cystadenocarcinoma, pancreatic adenocarcinoma, pheochromocytoma, paraganglioma, prostate adenocarcinoma, rectum adenocarcinoma, sarcoma, skin cutaneous melanoma, stomach adenocarcinoma, testicular germ cell tumors, thyroid carcinoma, thymoma, uterine carcinosarcoma, uveal melanoma. Other examples include breast cancer, lung cancer, lymphoma, melanoma, liver cancer, colorectal cancer, ovarian cancer, bladder cancer, renal cancer or gastric cancer. Further examples of cancer include neuroendocrine cancer, non-small cell lung cancer (NSCLC), small cell lung cancer, thyroid cancer, endometrial cancer, biliary cancer, esophageal cancer, anal cancer, salivary, cancer, vulvar cancer or cervical cancer.
The term “tumor” refers to all neoplastic cell growth and proliferation, whether malignant or benign, and all pre-cancerous and cancerous cells and tissues. The terms “cancer,” “cancerous,” “cell proliferative disorder,” “proliferative disorder” and “tumor” are not mutually exclusive as referred to herein.
EXAMPLES
The disclosure is further illustrated by the following examples, which are not to be construed as limiting this disclosure in scope or spirit to the specific procedures herein described. It is to be understood that the examples are provided to illustrate certain aspects and that no limitation to the scope of the disclosure is intended thereby. It is to be further understood that resort may be had to various other aspects, embodiments, modifications, and equivalents thereof which may suggest themselves to those skilled in the art without departing from the spirit of the present disclosure and/or scope of the appended claims.
Example 1. Derivation of a 13-Marker Gene Panel
Raw probe intensities from n=24 colon cancer tumor tissue samples were compared to n=22 control colon mucosa to identify genes that best discriminated between disease using the transcriptional profile of E-MTAB-57. Gene co-expression networks were generated to identify temporal patterns of gene regulation associated with colon cancer. A total of 513 nodes with 53,786 links were identified. Differential expression analysis identified 103 genes were upregulated in tumor tissue compared to blood. To identify blood-specific colon cancer gene biomarkers, we evaluated expression of the 103 genes in peripheral blood transcriptomes (n=7). Thirty-three (32%) of the 103 genes were below the level of detection in blood identifying these as candidate genes. Evaluation of transcripts in a preliminary dataset of blood samples from colon cancer (n=20) and matched normal blood (n=20) identified thirteen genes and one house-keeping gene as markers of colon cancer (Table 2). These genes were demonstrated to be highly expressed in colon cancer tumor tissue compared to normal mucosa and in three different colon cancer cell lines, LOVO (metastatic, hyperdiploid, MSI unstable cell line), LS-180 (derived from a Duke's B, colorectal adenocarcinoma) and Colo 320DM (derived from a Duke's C, colorectal adenocarcinoma). These data demonstrate target transcripts are produced by neoplastically transformed colon mucosal cells (FIGS. 1A-1B).
An artificial intelligence model of colon cancer disease was built using normalized gene expression of these 13 markers in whole blood from Controls (n=120) and Colon Cancers (n=272) samples. The dataset was randomly split into training and testing partitions for model creation and validation respectively. Twelve algorithms were evaluated (XGB, RF, glmnet, cforest, CART, treebag, knn, nnet, SVM-radial, SVM-linear, NB and mlp). The top performing algorithm (XGB—“gradient boosting”) best predicted the training data. In the test set, XGB produced probability scores that predicted the sample. Each probability score reflects the “certainty” of an algorithm that an unknown sample belongs to either “Control” or “Colon Cancer” class. For example, an unknown sample Si can have the following probability vector [Control=20%, Colon Cancer=80%]. This sample would be considered a colon cancer sample.
Example 2. Clinical Utility
The data (receiver operator cuver analysis and metrics) for the utility of the test to differentiate patients with colon cancer (n=136) from controls (n=60) in the training and test sets are included in FIGS. 2A-2B. The score exhibited an area under the curve (AUC) of 0.90 (training) and 0.86 (test set). The metrics are: sensitivity: 85.3-87.5% and specificity: 75-83.3%.
Overall, ColoTest scores were significantly elevated in cancers (63±1%) and controls (34±2%) (FIGS. 3A-3B). The overall accuracy (training and test cohort) is 84%, with an AUC: 0.88. The z-statistic for differentiating controls was 18.5.
A decision curve analysis was used to quantify the clinical benefit of the diagnostic test (FIGS. 4A-4B). The ColoTest exhibited >50% standardized predictive benefit up to a risk threshold of 80%. The probit risk assessment plot identified a ColoTest score >50% was 75% accurate for predicting colon cancer in a blood sample. This was increased to >80% at a ColoTest score ≥60%. The tool can therefore accurately differentiate between controls and colon cancer disease.
Specific evaluation of a colon cancer cohort before and after surgery identified that complete removal of a tumor and no evidence of disease was associated with a significant decrease (p<0.0001) in the ColoTest (FIG. 5 ). Levels were not significantly different in those with evidence of residual disease.
Examination of a separate colon cancer cohort by disease status (clinical evaluation at time of blood-draw) identified that the ColoTest was not significantly different between stable (n=17: 56±7%) and progressive disease (n=32: 68±4%) (FIGS. 6A-6C). However, 12 of the 17 patients progressed with 3 months of blood collection. Those that did progress exhibited elevated ColoTest scores at time of blood draw (n=12: 73±4%) that were not different to those with progressive disease at time of blood draw (n=32: 68±4%) (FIGS. 6A-6C). Levels in patients with stable disease were significantly lower (n=5: 16±4%, p<0.0001). A direct comparison between the ColoTest and CEA in these samples identified that the gene expression assay was significantly more sensitive (p<0.05) than CEA for predicting disease progression (FIG. 7 ). The ColoTest tool can therefore accurately predict progressive colon cancer disease.
ROC analysis identified the ColoTest had an AUC: 0.97 for differentiating stable from progressive disease. The z-statistic for differentiating controls was 20.6. Further evaluation of this cohort identified that patients who exhibited disease progression despite therapy exhibited higher scores than those responding to therapy (FIG. 8 ). Therapies included bevacizumab, chemotherapy and EGFR TKI inhibitors. The tool can therefore accurately identify treatment failure in colon cancer disease.
TABLE 2
Colon Cancer Biomarker or
Housekeeping Genes NCBI Chromosome Amplicon Exon Assay
Symbol Name location UniGene ID RefSeq length Boundary Location
ADRM1 adhesion regulating Chr.20: 62302056- Hs.90107 NM_007002.3  60 3-4  486
molecule 1 62308862
CDK4 cyclin dependent Chr.12: 57747727- Hs.95577 NM_000075.3  65 5-6  928
kinase 4 57752447
COMT catechol-O- Chr.22: 19941740- Hs.370408 NM_000754.3 118 5-6  864
methyltransferase 19969975
DHCR7 7-dehydrocholesterol Chr.11: 71434411- Hs.503134 NM_001163817.1  74 3-4  351
reductase 71448431
HMOX2 heme oxygenase 2 Chr.16: 4474697- Hs.284279 NM_001127204.1  81 5-6 1002
4510347
MCM2 minichromosome Chr.3: 127598357- Hs.477481 NM_004526.3  67 13-14 2374
maintenance complex 127622436
component 2
MORF4L1 mortality factor 4 Chr.15: 78872781- Hs.374503 NM_001265603.1  62 1  116
(housekeeping like 1 78897739
gene)
PDXK pyridoxal (pyridoxine, Chr.21: 43719097- Hs.284491 NM_003681.4 103  9-10  959
vitamin B6) kinase 43762307
POP7 POP7 homolog, Chr.7: 100706053- Hs.416994 NM_005837.2 136 2  828
ribonuclease P/MRP 100707500
subunit
S100P S100 calcium binding Chr.4: 6693839- Hs.2962 NM_005980.2  73 1-2  234
protein P 6697170
SNRPA small nuclear Chr.19: 40750854- Hs.466775 NM_004596.4 123 3-4  986
ribonucleoprotein 40765392
polypeptide A
SORD sorbitol Chr.15: 45023104- Hs.878 NM_003104.5  72 4-5  601
dehydrogenase 45075089
STOML2 stomatin like 2 Chr.9: 35099776- Hs.3439 NM_001287031.1  68 2-3  290
35103195
UMPS uridine Chr.3: 124730366- Hs.2057 NM_000373.3  85 3-4 1082
monophosphate 124749273
synthetase
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EQUIVALENTS
While the present invention has been described in conjunction with the specific aspects set forth above, many alternatives, modifications and other variations thereof will be apparent to those of ordinary skill in the art. All such alternatives, modifications and variations are intended to fall within the spirit and scope of the present invention.

Claims (12)

The invention claimed is:
1. A method of treating colon cancer in a subject comprising:
determining the expression level of at least 14 biomarkers from a test sample from a subject by contacting the test sample with a plurality of agents specific to detect the expression of the at least 14 biomarkers, wherein the 14 biomarkers comprise ADRM1, CDK4, COMT, DHCR7, HMOX2, MCM2, PDXK, POP7, S100P, SNRPA, SORD, STOML2, UMPS, and a housekeeping gene, wherein the housekeeping gene is MORF4L1;
normalizing the expression level of each of ADRM1, CDK4, COMT, DHCR7, HMOX2, MCM2, PDXK, POP7, S100P, SNRPA, SORD, STOML2, and UMPS to the expression level of the housekeeping gene, thereby obtaining a normalized expression level of each of ADRM1, CDK4, COMT, DHCR7, HMOX2, MCM2, PDXK, POP7, S100P, SNRPA, SORD, STOML2, and UMPS;
inputting each normalized expression level into an algorithm to generate a score, wherein the algorithm is a product of a model of colon cancer disease derived using the XGB algorithm;
comparing the score with a predetermined cutoff value;
determining that the score is equal to or greater than the predetermined cutoff value, thereby identifying the subject as having colon cancer; and
administering to the subject identified as having colon cancer a therapy, wherein the therapy comprises anti-cancer therapy, chemotherapy, targeted drug therapy, radiation therapy, immunotherapy or any combination thereof.
2. The method of claim 1, wherein the predetermined cutoff value is at least 50% on a scale of 0-100%.
3. The method of claim 1, wherein the predetermined cutoff value is at least 60% on a scale of 0-100%.
4. The method of claim 1, wherein the predetermined cutoff value has a sensitivity of identifying the subject as having colon cancer that is greater than 85%.
5. The method of claim 1, wherein the predetermined cutoff value has a specificity of identifying the subject as having colon cancer that is greater than 75%.
6. The method of claim 1, wherein at least one of the at least 14 biomarkers is RNA, cDNA or protein.
7. The method of claim 6, wherein when the biomarker is RNA, the RNA is reverse transcribed to produce cDNA, and the produced cDNA expression level is detected.
8. The method of claim 1, wherein the predetermined cutoff value is derived from a plurality of reference samples obtained from subjects not having or not diagnosed with a colon cancer.
9. The method of claim 1, wherein therapy comprises chemotherapy, wherein the chemotherapy comprises FOLFOX, FOLFIRI, a combination of 5-FU and leucovorin, capecitabine, irinotecan, CapeOx or any combination thereof.
10. The method of claim 1, wherein when the therapy comprises targeted drug therapy, wherein the targeted drug therapy comprises bevacizumab, cetuximab, panitumumab, regorafenib, a combination of trifluridine and tipiracil, an EGFR TKI inhibitor or any combination thereof.
11. The method of claim 1, wherein when the therapy comprises anti-cancer therapy, wherein the anticancer therapy comprises anti-colon cancer therapy.
12. The method of claim 1, wherein when the therapy comprises immunotherapy, wherein the immunotherapy comprises pembrolizumab, nivolumab or a combination of pembrolizumab and nivolumab.
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